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

These data represent annual greenhouse gas (GHG) emission totals by industry sectors and households for the total U.S. and by state, for years 2012 to 2020. Industry sectors are defined by North American Industry Classification System (NAICS) 2012 codes, with additional codes added for households and government. Emissions of 16 different GHGs, which are the same GHGs as reported in the U.S. GHG Inventory, are included. Values are given in total kilograms emitted for the given year, sector and location. Data are provided in two alternative formats, as Excel files and as Apache parquet files. The Excel files include: 1) GHGs by 114 aggregate level sectors by state and year, 2) GHGs by 114 aggregate level sectors by year for the U.S., and 3) GHGs by 540 detailed sectors by year for the U.S. The Excel files use a simplified version (not all fields included) of the Flow-by-Sector format (see link to format specification below). The parquet files align with the Excel files except are also separated by year, and provide the complete flow by sector format, where files with "state_m1" correspond to the aggregate level state datasets, files with "national_m1" correspond to the aggregate level national dataset, and files with "national_m2" correspond to the aggregate level state datasets, Standard metadata files in JSON format, and log and validation files in text format (with .log extension) are provided for each parquet file. The data are a product of updated sector attribution models that improve upon the National Greenhouse Gas Industry Attribution Model. The models used to generate the national aggregate and the state datasets are sector attribution models coded in the FLOWSA v2.0.0 tool (https://github.com/USEPA/flowsa/tree/v2.0.0). The national detailed datasets are developed with FLOWSA v2.0.1 (https://github.com/USEPA/flowsa/tree/v2.0.1).

Frequency: Semi-annualTable: 33-10-0269-01Release date: 2020-08-13Geography: Census subdivision, Census metropolitan areaNorth American Industry Classification System (NAICS): Period 1 - 2020Symbol legend:.. / not available for a specific reference periodThe footnotes in the table are represented in brackets.1) Businesses are counted according to the number of statistical locations" they have. For example a retail business with 10 stores and a head office is counted 11 times in the Canadian business counts. Please consult our guide for more information."2) The data includes active Canadian locations with employees.3) Fluctuations in these figures from one reference period to another can come from methodological changes (for example, changes to the method for identifying inactive units or in business industrial classification strategies). As a result, these data do not only represent changes in the business population over time. Statistics Canada advises users not to use these data as a time series.4) The employment size ranges provided should not be used to calculate total number of employees.5) The 2017 version of the North American Industry Classification System (NAICS) is used for this table."Cite: Statistics Canada. Table 33-10-0269-01 Canadian Business Counts, with employees, census metropolitan areas and census subdivisions, June 2020https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=3310026901

Frequency: Semi-annualTable: 33-10-0269-01Release date: 2020-08-13Geography: Census subdivision, Census metropolitan areaNorth American Industry Classification System (NAICS): Period 1 - 2020Symbol legend:.. / not available for a specific reference periodThe footnotes in the table are represented in brackets.1) Businesses are counted according to the number of statistical locations" they have. For example a retail business with 10 stores and a head office is counted 11 times in the Canadian business counts. Please consult our guide for more information."2) The data includes active Canadian locations with employees.3) Fluctuations in these figures from one reference period to another can come from methodological changes (for example, changes to the method for identifying inactive units or in business industrial classification strategies). As a result, these data do not only represent changes in the business population over time. Statistics Canada advises users not to use these data as a time series.4) The employment size ranges provided should not be used to calculate total number of employees.5) The 2017 version of the North American Industry Classification System (NAICS) is used for this table."Cite: Statistics Canada. Table 33-10-0269-01 Canadian Business Counts, with employees, census metropolitan areas and census subdivisions, June 2020https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=3310026901

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

Three tables are provided of US commercial waste generation by NAICS codes for (1) Commercial non-hazardous waste (non-construction), (2) Commercial non-hazardous waste from construction, and (3) Commercial RCRA hazardous waste. The unique waste types within these three tables are defined in referenced sources. These national totals by NAICS are mapped to BEA (NAICS-based) detailed industries (388 total) from the BEA 2007 benchmark input-output tables. A crosswalk table is provided. Three satellite tables for the USEEIO model are provided using the mapped national waste totals and the industry gross output for the data year for that BEA industry after it has been adjusted to 2013 USD using the BEA industry-specific chain price index. See the associated manuscript for more details. The satellite table files are formatted for use in the USEEIO modeling framework (http://github.com/USEPA/useeio/) to incorporate into a USEEIO model. This dataset is associated with the following publication: Meyer, D.E., M. Li, and W.W. Ingwersen. Analyzing economy-scale solid waste generation using the United States environmentally-extended input-output model. Resources, Conservation and Recycling. Elsevier Science BV, Amsterdam, NETHERLANDS, 157: 104795, (2020).

Release Date: 2022-05-26.Release Schedule:..The CBP data in this file were released on April 28, 2022. The ZIP Code Business Patterns (ZBP) data were released on May 26, 2022...Key Table Information:..Beginning with reference year 2007, CBP and ZBP data are released using Noise Infusion to protect confidentiality. See CBP Methodology for complete information on the coverage and methodology of the County Business Patterns and ZBP data series..Includes only establishments with payrolls...Four employment-size classes (1,000 to 1,499 employees, 1,500 to 2,499 employees, 2,500 to 4,999 employees, and 5,000 or more employees) are only available at the CSA, MSA, and County-levels...ZBP data by employment size class, shown at the 2-6 digit NAICS code levels only contains data on the number of establishments. ZBP data shown for NAICS code 00 (Total for all sectors) contains data on the number of establishments, employment, first quarter payroll, and annual payroll. ..Data Items and Other Identifying Records: ..This file contains data classified by Legal Form of Organization (U.S. and state level only) and employment size category of the establishment...Number of establishments..Annual payroll ($1,000)..First-quarter payroll ($1,000)..Number of employees during the pay period containing March 12..Noise range for annual payroll, first-quarter payroll, and number of employees during the pay period including March 12 ..Geography Coverage:..The data are shown at the U.S. level and by State, County, Metropolitan/Micropolitan Statistical Areas, Combined Statistical Areas, 5-digit ZIP code, and Congressional District levels. Also available are data for the District of Columbia, Puerto Rico, and the Island Areas (American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, and the U.S. Virgin Islands) at the state and county equivalent-levels...Industry Coverage:..The data are shown at the 2- through 6- digit NAICS code levels for all sectors with published data, and for NAICS code 00 (Total for all sectors)...FTP Download:..Download the entire table at: https://www2.census.gov/programs-surveys/cbp/data/2020/CB2000CBP.zip ..API Information:..County Business Patterns (CBP) data are housed in the County Business Patterns (CBP) API. For more information, see CBP APIs...Methodology:..In accordance with U.S. Code, Title 13, Section 9, no data are published that would disclose the operations of an individual employer. The data are subject to nonsampling error such as errors of self-classification, as well as errors of response, nonreporting and coverage. 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 three contributing establishments are not presented. For detailed information about the methods used to collect and produce statistics, including sampling see CBP Methodology...Symbols:..D - Withheld to avoid disclosing data for individual companies; data are included in higher level totals (used prior to 2017) .G - Low noise; cell value was changed by less than 2 percent by the application of noise .H - Moderate noise; cell value was changed by 2 percent or more but less than 5 percent by the application of noise.J - High noise; cell value was changed by 5 percent or more by the application of noise.N - Not available or not comparable.S - Withheld because estimates did not meet publication standards.X - Not applicable.r - Revised .For a complete list of symbols, see CBP Glossary...Source:..U.S. Census Bureau, 2020 County Business Patterns.For more information about County Business Patterns, see CBP Website...Contact Information:..U.S. Census Bureau.Economy-Wide Statistics Division.Business Statistics Branch.Tel: (301) 763 - 2580 .Email: ewd.county.business.patterns@census.gov ..Note: The Census Bureau did not collect district boundaries for the 117th Congress, in keeping with the practice of not collecting the session which aligns with the decennial census. As a result, County Business Patterns estimates were tabulated using 116th Congressional districts and state and local geographies.

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

Frequency: Semi-annualTable: 33-10-0269-01Release date: 2020-08-13Geography: Census subdivision, Census metropolitan areaNorth American Industry Classification System (NAICS): Period 1 - 2020Symbol legend:.. / not available for a specific reference periodThe footnotes in the table are represented in brackets.1) Businesses are counted according to the number of statistical locations" they have. For example a retail business with 10 stores and a head office is counted 11 times in the Canadian business counts. Please consult our guide for more information."2) The data includes active Canadian locations with employees.3) Fluctuations in these figures from one reference period to another can come from methodological changes (for example, changes to the method for identifying inactive units or in business industrial classification strategies). As a result, these data do not only represent changes in the business population over time. Statistics Canada advises users not to use these data as a time series.4) The employment size ranges provided should not be used to calculate total number of employees.5) The 2017 version of the North American Industry Classification System (NAICS) is used for this table."Cite: Statistics Canada. Table 33-10-0269-01 Canadian Business Counts, with employees, census metropolitan areas and census subdivisions, June 2020https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=3310026901

Small business transactions and revenue data aggregated from several credit card processors, collected by Womply and compiled by Opportunity Insights. Transactions and revenue are reported based on the ZIP code where the business is located.

Data provided for CT (FIPS code 9), MA (25), NJ (34), NY (36), and RI (44).

Data notes from Opportunity Insights: Seasonally adjusted change since January 2020. Data is indexed in 2019 and 2020 as the change relative to the January index period. We then seasonally adjust by dividing year-over-year, which represents the difference between the change since January observed in 2020 compared to the change since January observed since 2019. We account for differences in the dates of federal holidays between 2019 and 2020 by shifting the 2019 reference data to align the holidays before performing the year-over-year division.

Small businesses are defined as those with annual revenue below the Small Business Administration’s thresholds. Thresholds vary by 6 digit NAICS code ranging from a maximum number of employees between 100 to 1500 to be considered a small business depending on the industry.

County-level and metro-level data and breakdowns by High/Middle/Low income ZIP codes have been temporarily removed since the August 21st 2020 update due to revisions in the structure of the raw data we receive. We hope to add them back to the OI Economic Tracker soon.

More detailed documentation on Opportunity Insights data can be found here: https://github.com/OpportunityInsights/EconomicTracker/blob/main/docs/oi_tracker_data_documentation.pdf

Three tables are provided of US commercial waste generation by NAICS codes for (1) Commercial non-hazardous waste (non-construction), (2) Commercial non-hazardous waste from construction, and (3) Commercial RCRA hazardous waste. The unique waste types within these three tables are defined in referenced sources.

These national totals by NAICS are mapped to BEA (NAICS-based) detailed industries (388 total) from the BEA 2007 benchmark input-output tables. A crosswalk table is provided.

Three satellite tables for the USEEIO model are provided using the mapped national waste totals and the industry gross output for the data year for that BEA industry after it has been adjusted to 2013 USD using the BEA industry-specific chain price index. See the associated manuscript for more details. The satellite table files are formatted for use in the USEEIO modeling framework (http://github.com/USEPA/useeio/) to incorporate into a USEEIO model.

This dataset is associated with the following publication: Meyer, D.E., M. Li, and W.W. Ingwersen. Analyzing economy-scale solid waste generation using the United States environmentally-extended input-output model. Resources, Conservation and Recycling. Elsevier Science BV, Amsterdam, NETHERLANDS, 157: 104795, (2020).

Key Table Information.Table Title.Annual Business Survey: Statistics for Employer Firms by Veteran Status for the U.S.: 2020.Table ID.ABSCS2020.AB00MYCSA01D.Survey/Program.Economic Surveys.Year.2020.Dataset.ECNSVY Annual Business Survey Company Summary.Release Date.2022-11-10.Release Schedule.The Annual Business Survey (ABS) occurs every year, beginning in reference year 2017.For more information about ABS planned data product releases, see Tentative ABS Schedule..Dataset Universe.The dataset universe consists of employer firms that are in operation for at least some part of the reference year, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees and annual receipts of $1,000 or more, and are classified in one of nineteen in-scope sectors defined by the 2017 North American Industry Classification System (NAICS), except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered..Sponsor.National Center for Science and Engineering Statistics, U.S. National Science Foundation.Methodology.Data Items and Other Identifying Records.Number of employer firms (firms with paid employees)Sales and receipts of employer firms (reported in $1,000s of dollars)Number of employees (during the March 12 pay period)Annual payroll (reported in $1,000s of dollars)These data are aggregated by the following demographic classifications of firm for:All firms Classifiable (firms classifiable by sex, ethnicity, race, and veteran status) Veteran Status (defined as having served in any branch of the U.S. Armed Forces) Veteran Equally veteran/nonveteran Nonveteran Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status) Definitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the ABS are employer companies or firms rather than establishments. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization..Geography Coverage.The data are shown for the U.S. only.For information about geographies, see Geographies..Industry Coverage.The data are shown for the total of all sectors ("00") NAICS code. Sector "00" is not an official NAICS sector but is rather a way to indicate a total for multiple sectors. Note: Other programs outside of ABS may use sector 00 to indicate when multiple NAICS sectors are being displayed within the same table and/or dataset.The following are excluded from the total of all sectors:Crop and Animal Production (NAICS 111 and 112)Rail Transportation (NAICS 482)Postal Service (NAICS 491)Monetary Authorities-Central Bank (NAICS 521)Funds, Trusts, and Other Financial Vehicles (NAICS 525)Religious, Grantmaking, Civic, Professional, and Similar Organizations (NAICS 813)Private Households (NAICS 814)Public Administration (NAICS 92)For information about NAICS, see North American Industry Classification System..Sampling.The ABS sample includes firms that are selected with certainty if they have known research and development activities, were included in the 2020 BERD sample, or have high receipts, payroll, or employment. Total sample size is 300,000 firms. The universe is stratified by state, industry group, and expected demographic group. Firms selected to the sample receive a questionnaire. For all data on this table, firms not selected into the sample are represented with administrative, 2017 Economic Census, or other economic surveys records.For more information about the sample design, see Annual Business Survey Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. P-7504866, Disclosure Review Board (DRB) approval number: CBDRB-FY22-308).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business' data or identity.To comply with data quality standards, data rows with high relative standard errors (RSE) are not presented. Additionally, firm counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the Annual Business Survey Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, and more, see Technical Documentation..Weights.For more information about weighting, see Annual Business Survey Methodology..Table Information.FTP Download.https://www2.census.gov/programs-surveys/abs/data/2020/.API Information.Annual Business Survey (ABS) data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing data for individual companies; data are included in hig...

Business practices tested or used while social distancing measures were in place, since March 15, 2020, by North American Industry Classification System (NAICS) code, business employment size, type of business and majority ownership.

The datasets are comprised of greenhouse gas (GHG) emission factors (Factors) for 1,016 U.S. commodities as defined by the 2017 version of the North American Industry Classification System (NAICS). The Factors are based on GHG data representing 2019. Factors are given for all NAICS-defined commodities at the 6-digit level except for electricity, government, and households. Each record consists of three factor types as in the previous releases: Supply Chain Emissions without Margins (SEF), Margins of Supply Chain Emissions (MEF), and Supply Chain Emissions with Margins (SEF+MEF). One set of Factors (SupplyChainGHGEmissionFactors_v1.2_NAICS_CO2e_USD2021.csv) provides kg carbon dioxide equivalents (CO2e) per USD for all GHGs combined using 100 yr global warming potentials from the 4th IPPC Assessment report to calculate the equivalents. In this dataset there is one SEF, MEF and SEF+MEF per commodity. The other dataset of Factors (SupplyChainGHGEmissionFactors_v1.2_NAICS_byGHG_USD2021.csv) provides kg of each unique GHG emitted per dollar per commodity without the CO2e calculation. The dollar (USD) in the denominator of all factors uses purchaser prices in 2021 USD. See the supporting file 'Aboutthe2019v1.2SupplyChainGHGEmissionFactors.pdf' for complete documentation of this dataset.

Length of time businesses reported being able to continue to operate without a source of revenue as of February 1, 2020, by North American Industry Classification System (NAICS) code, business employment size, type of business and majority ownership.

Analysis of ‘Womply State-level Business Revenue’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/de408fa1-0d08-420d-b877-2109891047d9 on 27 January 2022.

--- Dataset description provided by original source is as follows ---

Small business transactions and revenue data aggregated from several credit card processors, collected by Womply and compiled by Opportunity Insights. Transactions and revenue are reported based on the ZIP code where the business is located.

Data provided for CT (FIPS code 9), MA (25), NJ (34), NY (36), and RI (44).

Data notes from Opportunity Insights: Seasonally adjusted change since January 2020. Data is indexed in 2019 and 2020 as the change relative to the January index period. We then seasonally adjust by dividing year-over-year, which represents the difference between the change since January observed in 2020 compared to the change since January observed since 2019. We account for differences in the dates of federal holidays between 2019 and 2020 by shifting the 2019 reference data to align the holidays before performing the year-over-year division.

Small businesses are defined as those with annual revenue below the Small Business Administration’s thresholds. Thresholds vary by 6 digit NAICS code ranging from a maximum number of employees between 100 to 1500 to be considered a small business depending on the industry.

County-level and metro-level data and breakdowns by High/Middle/Low income ZIP codes have been temporarily removed since the August 21st 2020 update due to revisions in the structure of the raw data we receive. We hope to add them back to the OI Economic Tracker soon.

More detailed documentation on Opportunity Insights data can be found here: https://github.com/OpportunityInsights/EconomicTracker/blob/main/docs/oi_tracker_data_documentation.pdf

--- Original source retains full ownership of the source dataset ---

Analysis of ‘USA Monthly Retail Sales’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/landlord/usa-monthly-retail-trade on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Introduction

The dataset contains the Monthly sales for retail trade and food services in USA, adjusted and unadjusted for seasonal variations for various categories. These categories shows various kind of Business categories operating in USA. These categories are based on North American Industry Classification System (NAICS).

Dataset Description

• The dataset contains the estimates of Monthly Retail and Food Services Sales by Kind of Business from the year 1992 - 2020. These estimates are shown in millions of dollars and are based on data from the Monthly Retail Trade Survey, Annual Retail Trade Survey, * Service Annual Survey, and administrative records.
• Their are another to files that contain the monthly data for the code NAICS code 44X72: Retail Trade and Food Services: U.S. Total for both Seasonally Adjusted Sales and non Seasonally Adjusted Sales in Millions of Dollars from 1992 to 2020.
• An helper file for NAICS code for retail and food industry is also provided for reference

Acknowledgements

The Dataset was published on U.S. Census Bureau website (https://www.census.gov)

--- Original source retains full ownership of the source dataset ---

This extract lists job postings scraped from the web by Greenwich HR, a human resources intelligence company from the beginning of 2020. According to the company, the data represents more than 70% of the official job listings across various sectors. Raw extract files are obtained weekly from Greenwich HR in .part_00000 files which are read as tables. The extract contain information on company, job details, SIC and NAICS codes, post timestamp, skills sought, etc. SIC codes obtained in the extract are converted to 2 digit NAICS codes by selecting the first two digits and joining with two digits NAICS codes based on SIC-NAICS crosswalk search results. Data is aggregated weekly by counties and categorized according to two digit NAICS codes whenever possible. Change in number of listings is based on year on year values compared with weeks beginning the first day of each year. The data was also joined to county-wise montly employment data from Bureau of Labor Statistics.

Business practices tested or used while social distancing measures were in place, since March 15, 2020, by North American Industry Classification System (NAICS) code, business employment size, type of business and majority ownership.

Key Table Information.Table Title.Annual Business Survey: Statistics for Employer Firms by Sex for the U.S.: 2020.Table ID.ABSCS2020.AB00MYCSA01A.Survey/Program.Economic Surveys.Year.2020.Dataset.ECNSVY Annual Business Survey Company Summary.Release Date.2022-11-10.Release Schedule.The Annual Business Survey (ABS) occurs every year, beginning in reference year 2017.For more information about ABS planned data product releases, see Tentative ABS Schedule..Dataset Universe.The dataset universe consists of employer firms that are in operation for at least some part of the reference year, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees and annual receipts of $1,000 or more, and are classified in one of nineteen in-scope sectors defined by the 2017 North American Industry Classification System (NAICS), except for NAICS 111, 112, 482, 491, 521, 525, 813, 814, and 92 which are not covered..Sponsor.National Center for Science and Engineering Statistics, U.S. National Science Foundation.Methodology.Data Items and Other Identifying Records.Number of employer firms (firms with paid employees)Sales and receipts of employer firms (reported in $1,000s of dollars)Number of employees (during the March 12 pay period)Annual payroll (reported in $1,000s of dollars)These data are aggregated by the following demographic classifications of firm for:All firms Classifiable (firms classifiable by sex, ethnicity, race, and veteran status) Sex Female Male Equally male/female Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status) Definitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the ABS are employer companies or firms rather than establishments. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization..Geography Coverage.The data are shown for the U.S. only.For information about geographies, see Geographies..Industry Coverage.The data are shown for the total of all sectors ("00") NAICS code. Sector "00" is not an official NAICS sector but is rather a way to indicate a total for multiple sectors. Note: Other programs outside of ABS may use sector 00 to indicate when multiple NAICS sectors are being displayed within the same table and/or dataset.The following are excluded from the total of all sectors:Crop and Animal Production (NAICS 111 and 112)Rail Transportation (NAICS 482)Postal Service (NAICS 491)Monetary Authorities-Central Bank (NAICS 521)Funds, Trusts, and Other Financial Vehicles (NAICS 525)Religious, Grantmaking, Civic, Professional, and Similar Organizations (NAICS 813)Private Households (NAICS 814)Public Administration (NAICS 92)For information about NAICS, see North American Industry Classification System..Sampling.The ABS sample includes firms that are selected with certainty if they have known research and development activities, were included in the 2020 BERD sample, or have high receipts, payroll, or employment. Total sample size is 300,000 firms. The universe is stratified by state, industry group, and expected demographic group. Firms selected to the sample receive a questionnaire. For all data on this table, firms not selected into the sample are represented with administrative, 2017 Economic Census, or other economic surveys records.For more information about the sample design, see Annual Business Survey Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. P-7504866, Disclosure Review Board (DRB) approval number: CBDRB-FY22-308).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business' data or identity.To comply with data quality standards, data rows with high relative standard errors (RSE) are not presented. Additionally, firm counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the Annual Business Survey Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, and more, see Technical Documentation..Weights.For more information about weighting, see Annual Business Survey Methodology..Table Information.FTP Download.https://www2.census.gov/programs-surveys/abs/data/2020/.API Information.Annual Business Survey (ABS) data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsS - Estimate does not meet publication standards because of high sampling variability,...