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 Series Title: Employment Level: State, White, Age 16-24: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Yearly Chart  |  Excel file  |  Self-updating Excel file
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 2003 01  22424·
 2003 02  60427·
 2003 03  24403·
 2003 04  6455.
 2003 05  19375.
 2003 06  81326·
 2003 07  9306.
 2003 08  52323.
 2003 09  39377·
 2003 10  56416·
 2003 11  51390.
 2003 12  53395.
 2004 01 31333.
 2004 02 68370·
 2004 03 62423·
 2004 04 52420·
 2004 05 72369·
 2004 06 23357.
 2004 07 82329.
 2004 08 21366·
 2004 09 61389·
 2004 10 53494·
 2004 11 73460·
 2004 12 51429·
 2005 01  25368.
 2005 02  14357·
 2005 03  22382·
 2005 04  63382.
 2005 05  13388·
 2005 06  88330·
 2005 07  43342.
 2005 08  0317·
 2005 09  1375.
 2005 10  81437.
 2005 11  73389.
 2005 12  33386·
 2006 01 90400.
 2006 02 26432·
 2006 03 76476·
 2006 04 54495.
 2006 05 4422.
 2006 06 79352·
 2006 07 39354·
 2006 08 83354·
 2006 09 94350.
 2006 10 21362·
 2006 11 76378·
 2006 12 64425.
 2007 01  36413.
 2007 02  59484·
 2007 03  23477.
 2007 04  67477·
 2007 05  30417.
 2007 06  24387·
 2007 07  44378·
 2007 08  85338.
 2007 09  0403·
 2007 10  75434.
 2007 11  27452·
 2007 12  38485.
 2008 01 99398·
 2008 02 91360·
 2008 03 85367·
 2008 04 70368.
 2008 05 1347·
 2008 06 80403·
 2008 07 56385.
 2008 08 49395·
 2008 09 6407·
 2008 10 73466·
 2008 11 2472.
 2008 12 70482.
 2009 01  40515.
 2009 02  28511·
 2009 03  11571·
 2009 04  53572·
 2009 05  53491·
 2009 06  25456.
 2009 07  97419·
 2009 08  41388.
 2009 09  21381.
 2009 10  71444.
 2009 11  97446.
 2009 12  3437.
 2010 01 44417·
 2010 02 98456·
 2010 03 74469·
 2010 04 34470.
 2010 05 47380·
 2010 06 62330.
 2010 07 16373·
 2010 08 53366·
 2010 09 81451·
 2010 10 46359·
 2010 11 36394·
 2010 12 3400·
 2011 01  21339.
 2011 02  56415.
 2011 03  71409.
 2011 04  55456·
 2011 05  68394·
 2011 06  23375·
 2011 07  86348·
 2011 08  2347.
 2011 09  46367·
 2011 10  4364·
 2011 11  66373·
 2011 12  62328.
 2012 01 7331·
 2012 02 81351·
 2012 03 27362.
 2012 04 82387.
 2012 05 26345·
 2012 06 60270.
 2012 07 4270·
 2012 08 29295·
 2012 09 3317.
 2012 10 73346·
 2012 11 62416·
 2012 12 97461.
 2013 01  64413.
 2013 02  77433.
 2013 03  88472.
 2013 04  7435·
 2013 05  58320·
 2013 06  53356.
 2013 07  95371·
 2013 08  1406·
 2013 09  62461.
 2013 10  8469·
 2013 11  20419·
 2013 12  50413.
 2014 01 75413.
 2014 02 74421.
 2014 03 28471·
 2014 04 47498·
 2014 05 24388.
 2014 06 7394·
 2014 07 5447·
 2014 08 11416.
 2014 09 58436·
 2014 10 89450.
 2014 11 64450.
 2014 12 87397·
 2015 01  53414.
 2015 02  26441.
 2015 03  45434·
 2015 04  44459.
 2015 05  9430·
 2015 06  50426·
 2015 07  8414·
 2015 08  75418·
 2015 09  51516.
 2015 10  19559.
 2015 11  43595·
 2015 12  1539.
 2016 01 31441·
 2016 02 12475.
 2016 03 61464.
 2016 04 64482·
 2016 05 23440.
 2016 06 38368·
 2016 07 2366.
 2016 08 35406.
 2016 09 28436·
 2016 10 27448·
 2016 11 28515·
 2016 12 7496·
 2017 01  72495·
 2017 02  37509.
 2017 03  26495·
 2017 04  0496·
 2017 05  4404.
 2017 06  49419.
 2017 07  10392.


 2017 08  57354.
 2017 09  99447.
 2017 10  69487·
 2017 11  18508·
 2017 12  48485·
 2018 01 60555·
 2018 02 29596.
 2018 03 12532.
 2018 04 67508.
 2018 05 10378·
 2018 06 87358.
 2018 07 81375·
 2018 08 34373.
 2018 09 0402·
 2018 10 23446.
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US Unemployment Rate: Alternative Measures of Labor Underutilization

Charts

Unemployment Rate and Alternative Measures of Labor Underutilization
Unemployment Rate: Gender
Unemployment Rate: Black: Gender
Unemployment Rate: White: Gender
Unemployment Rate: Race
Unemployment Rate: Age: 16/25/35/45/55
Unemployment Rate: Education
Unemployment Rate: Nonagricultural Industry
Unemployment Rate: Job Category
Median Weeks Unemployed: Age
Median Weeks Unemployed: Race


The US Labor Force Dataset from the BLS contains nearly 15,000 series.
These series are subcategories of the popular series of:

Civilian Labor Force (subcategories)
Employment Level (subcategories)
Unemployment Level (subcategories)
US Unemployment Rate (subcategories)
Population (subcategories)
Employment-Population Ratio (subcategories)
Median Weeks Unemployed (subcategories)
Percent Distribution (subcategories)
Average Hours At Work (subcategories)
Of Total Unemployed (subcategories)

These basic measures are augmented by:

Population
Labor Force Participation Rate
Employment-Population Ratio
Not in Labor Force
Number at work
Average hours at work
Multiple jobholders
Average number of search methods used
Number At work part-time

These series can be subdivided by:

Sex:

Male
Female

Race and Ethnicity:

White
Black
Hispanic
Mexican
Puerto Rican
Cuban

Age:

16 years and over (default)
14_yrs._&_over
16-17_yrs.
16-19_yrs.
16-21_yrs.
16-24_yrs.
18-19_yrs.
20_yrs._&_over
20-24_yrs.
20-64_yrs.
25_yrs._&_over
25-29_yrs.
25-34_yrs.
25-54_yrs.
25-59_yrs.
30-34_yrs.
35-39_yrs.
35-44_yrs.
40-44_yrs.
45_yrs._&_over
45-49_yrs.
45-54_yrs.
50-54_yrs.
55_yrs._&_over
55-59_yrs.
55-64_yrs.
60-61_yrs.
60-64_yrs.
62-64_yrs.
65_yrs._&_over
65-69_yrs.
70_yrs._&_over

Class Of Worker:

Wage_And_Salary_Workers
Private_Wage_And_Salary_Workers
Government_Wage_And_Salary_Workers
Self-employed_Workers
Unpaid_Family_Workers

Industry:

Agriculture_Service
Furniture_And_Fixtures
Motor_Vehicles_&_Motor_Vehicle_Equipment
Aircraft
Tobacco
Eating_And_Drinking
Private_Households
Hospital
Postal
Federal
State
Local
Goods_Producing
Service_Producing
Agriculture_(Excludes_Forestry_And_Fisheries)
Forestry_And_Fisheries
Nonagricultural
Mining
Construction
Manufacturing
Manufacturing,_Durables
Lumber_And_Wood_Products,_Except_Furniture
Stone,_Clay,_And_Glass_Products
Primary_Metal
Fabricated_Metal
Machinery
Electrical_machinery,_equipment,_&_supplies
Transportation_Equipment
Professional_&_photographic_equipment_&_watches
Other_transportation_equipment
Fabricated_Metals
Manufacturing,_Nondurables
Food_And_Kindred_Products
Textile_Mill_Products
Apparel_And_Other_Fabricated_Textile_Products
Paper_And_Allied_Products
Printing,_Publishing,_And_Allied_Industries
Chemicals_And_Allied_Products
Petroleum_And_Coal_Products
Rubber_And_Miscellaneous_Plastic_Products
Leather_And_Leather_Products
Transportation,_Communication,_And_Other_Public_Utilities
Transportation
Transportation_Other_Than_Railroad_And_Railway_Express
Communications_And_Other_Public_Utilities
Communications
Trade
Wholesale_Trade
Retail_Trade
Service_Industries
Finance,_Insurance,_And_Real_Estate
Insurance_And_Real_Estate
Banking_And_Other_Financial_Organizations
Business_And_Repair_Services
Businesses
Repair_Services
Personal_Services
Entertainment_And_Recreation_Services
Professional_And_Related_Services
Medical
Educational_Services
Welfare_And_Religious_Services
Public_Administration

Occupation:

Managerial_&_professional_specialty_occupation
Executive,_administration,_&_managerial
Officials_&_administration,_public_administation
Management_Related_Occupations
Professional_Specialty_Occupations
Engineers
Math_&_Computer_Scientists
Natural_scientists
Health_Diagnosing_Occupations
Health_Assessment_&_Treating
Teachers,_college_&_university
Lawyers_&_Judges
Technical,_sales,_administration_support
Technicians_&_related_support_occupations
Health_technologists_&_technicians
Engineering_&_science_technicians
Technicians
Sales_Occupations
Supervisors_&_Proprietors
Sales_reps,_finance_&_business_services
Sales_reps,_commodities
Sales,_retail_&_personal
Sales_Related_Occupations
Administrative_support
Supervisors
Computer_Equipment_Operators
Secretaries,_stenographers,_&_typists
Financial_Records_Processing
Mail_&_Message_Distributing
Service_Occupation
Private_Household
Protective_Services
Food_Service
Health_Service
Cleaning_&_Building_Service
Personal_Service
Precision_Production,_Craft,_Repair
Mechanics_&_Repairers
Construction_Trades
Operators,_Fabricators,_Laborers
Machine_operators,_assemblers,_inspectors
Operators_&_tenders
Fabricators,_assemblers,_inspectors,_samplers
Transportation,_material_moving
Motor_vehicle_operators
Handlers,_equipment_cleaners,_helpers,_laborers
Construction_Laborers
Freight,_stock_material_handlers
Farming,_Forestry,_Fishing
Farm_Operators_&_Managers
Farm_workers_&_related_occupations
Forestry_&_fishing_occupations

Input your search text below.
or alter the examples after this blank template.







      Example 1: Get Unemployment Rates for people in Computer jobs







      Example 2: Get Employment Data for Workers in the "Retail Trade" Industry







      Example 3: Get Population Level Data for Workers





 Series Title: Employment Level: State, White, Age 16-24: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
   Transform this series  |  Display series in COPY/PASTE format  |  More series like this one

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