This layer contains the latest 14 months of unemployment statistics from the U.S. Bureau of Labor Statistics (BLS). The data is offered at the nationwide, state, and county geography levels. Puerto Rico is included. These are not seasonally adjusted values.The layer is updated monthly with the newest unemployment statistics available from BLS. There are attributes in the layer that specify which month is associated to each statistic. Most current month: December 2024 (preliminary values at the county level)The attributes included for each month are:Unemployment rate (%)Count of unemployed populationCount of employed population in the labor forceCount of people in the labor forceData obtained from the U.S. Bureau of Labor Statistics. Data downloaded: March 17th, 2025Local Area Unemployment Statistics table download: https://www.bls.gov/lau/#tablesLocal Area Unemployment FTP downloads:State and CountyNationData Notes:This layer is updated automatically when the BLS releases their most current monthly statistics. The layer always contains the most recent estimates. It is updated within days of the BLS's county release schedule. BLS releases their county statistics roughly 2 months after-the-fact. The data is joined to 2023 TIGER boundaries from the U.S. Census Bureau.Monthly values are subject to revision over time.For national values, employed plus unemployed may not sum to total labor force due to rounding.As of the January 2022 estimates released on March 18th, 2022, BLS is reporting new data for the two new census areas in Alaska - Copper River and Chugach - and historical data for the previous census area - Valdez Cordova.As of the March 17th, 2025 release, BLS now reports data for 9 planning regions in Connecticut rather than the 8 previous counties.To better understand the different labor force statistics included in this map, see the diagram below from BLS:

This map shows how the unemployment rate has changed in the US over the past year. This can be seen by counties within this map. The map shows if a county's unemployment rate has increased or decreased, and the size of the circles shows by how much. The colors are then shown with transparency behind the centroid to reinforce the pattern in areas where the change may have been smaller. The map always represents the most current figures offered by BLS, and updates automatically. To see the most current month offered by BLS, find the CurrentMonth attribute in the data table, or visit the metadata for the Living Atlas layer used in this map.Bureau of Labor Statistics (BLS):https://www.bls.gov/Local Area Unemployment Statistics (LAUS):https://www.bls.gov/lau/

The Consumer Price Index (CPI) is a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services. Indexes are available for the U.S. and various geographic areas. Average price data for select utility, automotive fuel, and food items are also available. Prices for the goods and services used to calculate the CPI are collected in 75 urban areas throughout the country and from about 23,000 retail and service establishments. Data on rents are collected from about 43,000 landlords or tenants. More information and details about the data provided can be found at http://www.bls.gov/cpi

This data shows a summary of annual unemployment rates for cities within the metro Phoenix area and supports Tempe's Unemployment Rate performance measure.The performance measure page is available at 5.13 Unemployment Rate. Additional InformationSource: https://www.bls.gov/Contact (author): Madalaine McConvilleContact E-Mail (author): madalaine_mcconville@tempe.govContact (maintainer): Contact E-Mail (maintainer): Data Source Type: Excel tablePreparation Method: Extracted for selected citiesPublish Frequency: AnnualPublish Method: ManualData Dictionary

This layer contains 2010-2014 American Community Survey (ACS) 5-year data, and contains estimates and margins of error. The layer shows median earnings by occupational group. This is shown by tract, county, and state boundaries. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Only full-time year-round workers included. Median earnings is based on earnings in past 12 months of survey. Occupation Groups based on Bureau of Labor Statistics (BLS)' Standard Occupation Classification (SOC). This layer is symbolized to show median earnings of the full-time, year-round civilian employed population. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Vintage: 2010-2014ACS Table(s): B24021 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: November 28, 2020National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census: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 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 Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer has associated layers containing the most recent ACS data available by the U.S. Census Bureau. Click here to learn more about ACS data releases and click here for the associated boundaries layer. The reason this data is 5+ years different from the most recent vintage is due to the overlapping of survey years. It is recommended by the U.S. Census Bureau to compare non-overlapping datasets.Boundaries come from the US Census TIGER geodatabases. Boundary vintage (2014) appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Interactive visualization of Carroll County facts and figures, including population, demographics, community involvement, economy, employment, education, housing, health, crime and transportation. Data sources include AARP, U.S. Census/ACS, ARC, BLS, Center for Neighborhood Technology and County Health Rankings.

Interactive visualization of Rockdale County facts and figures, including population, demographics, community involvement, economy, employment, education, housing, health, crime and transportation. Data sources include AARP, U.S. Census/ACS, ARC, BLS, Center for Neighborhood Technology and County Health Rankings.

Interactive visualization of Hall County facts and figures, including population, demographics, community involvement, economy, employment, education, housing, health, crime and transportation. Data sources include AARP, U.S. Census/ACS, ARC, BLS, Center for Neighborhood Technology and County Health Rankings.

This layer shows figures of quit rates and quit levels by the US, BLS regions, and states. Data is from the Bureau of Labor Statistics (BLS) and was released October and November of 2021. The layer default symbology highlights to September 2021 quit rate in comparison to the national figure of 3.0%.According to the October 2021 News Release by BLS:"The number of quits increased in August to 4.3 million (+242,000). The quits rate increased to a series high of 2.9 percent. Quits increased in accommodation and food services (+157,000); wholesale trade (+26,000); and state and local government education (+25,000). Quits decreased in real estate and rental and leasing (-23,000). The number of quits increased in the South and Midwest regions."In the following November News Release:"In September, quits rates increased in 15 states and decreased in 10 states. The largest increases in quits rates occurred in Hawaii (+3.8 percentage points), Montana (+1.5 points), as well as Nevada and New Hampshire (+1.1 points each). The largest decreases in quits rates occurred in Kentucky (-1.1 percentage points), Iowa (-1.0 point), and South Dakota (-0.7 point). Over the month, the national quits rate increased (+0.1 percentage point)."Quit rates: The quits rate is the number of quits during the entire month as a percent of total employment.Quit levels: Quits are the number of quits during the entire month.State and US figures: Table 4. Quits levels and rates by industry and region, seasonally adjustedRegion figures: Table 4. Quits levels and rates by industry and region, seasonally adjustedThis data was obtained in October and November 2021, and the months of data from BLS are as follows:August 2020September 2020April 2021 (only offered for Regions)May 2021June 2021July 2021August 2021September 2021 (preliminary values)For the full data release, click here.The states (including the District of Columbia) that comprise the regions are: Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and VermontSouth: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West VirginiaMidwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and WisconsinWest: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming.

Reference Layer: Bureau of Labor Statistics Monthly Unemployment (latest 14 months)_This layer contains the latest 14 months of unemployment statistics from the U.S. Bureau of Labor Statistics (BLS). The data is offered at the nationwide, state, and county geography levels. Puerto Rico is included. These are not seasonally adjusted values.The layer is updated monthly with the newest unemployment statistics available from BLS. There are attributes in the layer that specify which month is associated to each statistic. Most current month: August 2022 (preliminary values at the county level)The attributes included for each month are:Unemployment rate (%)Count of unemployed populationCount of employed population in the labor forceCount of people in the labor forceData obtained from the U.S. Bureau of Labor Statistics. Data downloaded: October 21, 2022Local Area Unemployment Statistics table download: https://www.bls.gov/lau/#tablesLocal Area Unemployment FTP downloads:State and CountyNationData Notes:This layer is updated automatically when the BLS releases their most current monthly statistics. The layer always contains the most recent estimates. It is updated within days of the BLS's county release schedule. BLS releases their county statistics roughly 2 months after-the-fact. The data is joined to 2021 TIGER boundaries from the U.S. Census Bureau.Monthly values are subject to revision over time.For national values, employed plus unemployed may not sum to total labor force due to rounding.As of the January 2022 estimates released on March 18th, BLS is reporting new data for the two new census areas in Alaska - Copper River and Chugach - and historical data for the previous census area - Valdez Cordova.To better understand the different labor force statistics included in this map, see the diagram below from BLS:

Unemployment Data by Age (Percent) 2017 to Present

  Current population Survey results showing unemployment data broken out by age. Presented in percents; seasonally adjusted, quarterly from 2017 to present. About the BLS Unemployment Data including Current Population Survey Demographic Breakdowns: Links to several different datasets, including Current Population Survey results showing seasonally adjusted unemployment data broken out by ethnicity and age, reason for unemployment, and duration of employment prior to unemployment for years including 2017-2019.  Other datasets show over-the-year percent change in the third month's employment level and taxable wages by industry for a given quarter at the County, State, and MSA level yearly from 1990 - present.
  Geography Level: NationalItem Vintage: 2017-Present
  Update Frequency: N/AAgency: BLSAvailable File Type: Excel 

  Return to Other Federal Agency Datasets Page

This map service was created to support the National Oceanic and Atmospheric Administration (NOAA) Office for Coastal Management’s (OCM) Coastal Flood Exposure Mapper. The purpose of the online mapping tool is to provide coastal managers, planners, and stakeholders a preliminary look at exposures to coastal flooding hazards. The Mapper is a screening-level tool that uses nationally consistent data sets and analyses. Data and maps provided can be used at several scales to help communities initiate resilience planning efforts. As with all remotely sensed data, all features should be verified with a site visit. The dataset is provided "as is," without warranty to its performance, merchantable state, or fitness for any particular purpose. The entire risk associated with the results and performance of this dataset is assumed by the user. This dataset should be used strictly as a planning reference and not for navigation, permitting, or other legal purposes. For more information, visit the Coastal Flood Exposure Mapper (https://coast.noaa.gov/floodexposure).Send questions or comments to the NOAA Office for Coastal Management (coastal.info@noaa.gov).

Quarterly Percent Change in 3rd Month Employment Level Data 1990 - Present

  Over-the-year percent change in the third month's employment level of a given quarter (Rounded to the tenths place). County, state, and MSA level, by industry, yearly from 1990 - present. About the BLS Unemployment Data including Current Population Survey Demographic Breakdowns: Links to several different datasets, including Current Population Survey results showing seasonally adjusted unemployment data broken out by ethnicity and age, reason for unemployment, and duration of employment prior to unemployment for years including 2017-2019.  Other datasets show over-the-year percent change in the third month's employment level and taxable wages by industry for a given quarter at the County, State, and MSA level yearly from 1990 - present.
  Geography Level: State, County, MSAItem Vintage: 1990-Present
  Update Frequency: YearlyAgency: BLSAvailable File Type: Website link to CSV/Excel/Legacy Flat files download 

  Return to Other Federal Agency Datasets Page

Reason for Unemployment Data

  Current population Survey results showing unemployment data detailing the reason for unemployment. Presented in thousands; seasonally adjusted, quarterly from 2017 to present. About the BLS Unemployment Data including Current Population Survey Demographic Breakdowns: Links to several different datasets, including Current Population Survey results showing seasonally adjusted unemployment data broken out by ethnicity and age, reason for unemployment, and duration of employment prior to unemployment for years including 2017-2019.  Other datasets show over-the-year percent change in the third month's employment level and taxable wages by industry for a given quarter at the County, State, and MSA level yearly from 1990 - present.
  Geography Level: NationalItem Vintage: Not Available
  Update Frequency: N/AAgency: BLSAvailable File Type: Excel 

  Return to Other Federal Agency Datasets Page

Unemployment Data by Ethnicity and Race 2019-2020

  Current Population Survey results showing unemployment data broken out by ethnicity and ages. Presented in percentages; non-seasonally adjusted, for the second quarter in 2019 and 2020. About the BLS Unemployment Data including Current Population Survey Demographic Breakdowns: Links to several different datasets, including Current Population Survey results showing seasonally adjusted unemployment data broken out by ethnicity and age, reason for unemployment, and duration of employment prior to unemployment for years including 2017-2019.  Other datasets show over-the-year percent change in the third month's employment level and taxable wages by industry for a given quarter at the County, State, and MSA level yearly from 1990 - present.
  Geography Level: NationalItem Vintage: 2019-2020
  Update Frequency: N/AAgency: BLSAvailable File Type: Excel 

  Return to Other Federal Agency Datasets Page

This data show the number of temporary US Census Bureau employees hired in each state to assist with the 2020 Census.Every ten year, the U.S. Constitution requires that the country’s population be counted. For 2020, the undertaking includes hiring as many as 500,000 temporary workers to conduct door-to-door field operations.The number of workers hired during peak Census Bureau operations is so large that it affects statistics about the nation's employment. Census employment data is important because it allows economists to remove the hires from economic indicator releases to better judge payroll trends and broader economic performance.Current Employment Statistics (CES) for the nation, states and metro areas are published each month by the U.S. Bureau of Labor Statistics (BLS). The statistics are based on a survey of businesses and government agencies.As a supplement to this release BLS will publish 2020 Census and CES Employment by State, providing month-to-month state-level tallies of Census hiring.

This app contains the latest 14 months of unemployment statistics from the U.S. Bureau of Labor Statistics (BLS). The data is offered at the nationwide, state, and county geography levels. Puerto Rico is included. These are not seasonally adjusted values. The layer is updated monthly with the newest unemployment statistics available from BLS. There are attributes in the layer that specify which month is associated to each statistic. Most current month: March 2021 (preliminary values at the state and county level)The attributes included for each month are:Unemployment rate (%)Count of unemployed populationCount of employed population in the labor forceCount of people in the labor forceData obtained from the U.S. Bureau of Labor Statistics. Local Area Unemployment Statistics table download: https://www.bls.gov/lau/#tablesLocal Area Unemployment FTP downloads:State and CountyNationData Notes:This layer is updated automatically when the BLS releases their most current monthly statistics. The layer always contains the most recent estimates. It is updated within days of the BLS's county release schedule. BLS releases their county statistics roughly 2 months after-the-fact. The data is joined to 2019 TIGER boundaries from the U.S. Census Bureau.Monthly values are subject to revision over time.For national values, employed plus unemployed may not sum to total labor force due to rounding.To better understand the different labor force statistics included in this map, see the diagram below from BLS:Esri's U.S. Updated Demographic Data - Population, age, income, sex, race, home value, and marital status are among the variables included in the database. Each year, Esri's Data Development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of U.S. geographies.Data Note: The median household income value divides the distribution of household income into two equal parts. Pareto interpolation is used if the median falls in an income interval other than the first or last. For the lowest interval, <$10,000, linear interpolation is used. If the median falls in the upper income interval of $500,000+, it is represented by the value of $500,001. Additional Esri Resources:Esri DemographicsU.S. 2020/2025 Esri Updated DemographicsEssential demographic vocabularyPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

This layer shows median earnings by occupational group broken down by sex. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Only full-time year-round workers included. Median earnings is based on earnings in past 12 months of survey. Occupation Groups based on Bureau of Labor Statistics (BLS)' Standard Occupation Classification (SOC). This layer is symbolized to show median earnings of the full-time, year-round civilian employed population. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B24022 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census: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 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 Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

This layer contains county-level unemployment claim data from the Tennessee Department of Labor for the period from March 14, 2020 through July 3, 2021. A feature and related attributes is provided for each county and for each week during this timeframe (95 counties x 69 weeks). Use the WEEK_END field to view data for an individual week. Data are not seasonally adjusted.In addition to the claims data, several groups of fields are provided to help classify the data by location and time:County Classification fieldsCounty name (NAMELSAD)County FIPS code (GEOID)Core-based statistical area code (CBSAFP)Core-based statistical area name (CBSAFP)Metropolitan/Micropolitan Classification (MSA_TYPE)MSA county type (MSA_COUNTY_TYPE)Local Workforce Development Area (LWDA_NAME)Local Workforce Development Area Acronym (LWDA_ACRONYM)TN ECD Urban/Rural Classification (URBAN_RURAL)Time ClassificationsDate Value (DATE_VALUE)Year (YEAR)Month of Year (MONTH)Week of Year (WEEK)ClaimsInitial Claims (INITIAL)Initial Claims Previous Week (INITIAL_PREVWK)Continued Claims (CONTINUED)Continued Claims Previous Week (CONT_PREVWK)BLS Labor Force for Month of Year (LAB_FORCE)

This feature service contains employment and wage data for detailed farming, fishing, and forestry occupations by nation, state, and metropolitan and nonmetropolitan areas. Data from Bureau of Labor Statistics' (BLS) Occupation Employment Statistics (OES) series. Data vintage: May 2018.Boundary files came from U.S. Census Bureau's 2018 Cartographic Boundary Files. Nonmetropolitan areas were constructed based on BLS' May 2018 Area Definitions.A few Frequently Asked Questions from BLS' OES FAQ site:How are "employees" defined by the OES Survey? "Employees" are all part-time and full-time workers who are paid a wage or salary. The survey does not cover the self-employed, owners and partners in unincorporated firms, household workers, or unpaid family workers.Do OES wage estimates include benefits? No. OES wage estimates represent wages and salaries only, and do not include nonproduction bonuses or employer costs of nonwage benefits, such as health insurance or employer contributions to retirement plans. Information on cost of benefits, benefit incidence, and detailed plan provisions is available from the National Compensation Survey program.Why does the sum of the areas within a state not equal the statewide employment? The sum of the areas may differ from statewide employment for several reasons:RoundingThe totals include data items that are not released separately due to confidentiality and quality reasons.Many States include metropolitan areas that cross State lines. These cross-State metropolitan area estimates include data from each State, which should not be included in a total for a single State.A small number of establishments indicate the State in which their employees are located, but do not indicate the specific metropolitan or nonmetropolitan area in which they are located. Data for these establishments are used in the calculation of the statewide estimates, but are not included in the estimates of any individual area.Why don't the major group or "all occupations" employment totals equal the sum of the employment estimates for the detailed occupations? The major group and "all occupations" totals may include detailed occupations for which separate employment estimates could not be published. As a result, employment totals at the major group and "all occupations" levels may be greater than the sum of employment estimates for the detailed occupations. Because the major group employment totals include employment for the detailed occupations in that group, summing across both detailed occupations and major groups will result in double counting of occupational employment.