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 Series Title: Employment Level: Pvt W/S Workers, Retail trade Industry, Asian, Age 16-24: NSA
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 2003 01  9127·
 2003 02  1597.
 2003 03  5695·
 2003 04  48116·
 2003 05  28123·
 2003 06  40151.
 2003 07  26171·
 2003 08  59170·
 2003 09  95144·
 2003 10  44145·
 2003 11  77156.
 2003 12  51167.
 2004 01 60161·
 2004 02 10103.
 2004 03 24110·
 2004 04 67115.
 2004 05 98140.
 2004 06 43159.
 2004 07 3153·
 2004 08 76151·
 2004 09 9129·
 2004 10 76128·
 2004 11 79134·
 2004 12 73124·
 2005 01  20122·
 2005 02  66117.
 2005 03  38136·
 2005 04  76135·
 2005 05  8199.
 2005 06  93128.
 2005 07  94138·
 2005 08  29134.
 2005 09  66114·
 2005 10  65124.
 2005 11  84125·
 2005 12  3135·
 2006 01 77106.
 2006 02 13101.
 2006 03 71127.
 2006 04 90110.
 2006 05 38102.
 2006 06 94127·
 2006 07 44156.
 2006 08 10167.
 2006 09 1134.
 2006 10 90134.
 2006 11 15112·
 2006 12 7104.
 2007 01  4088.
 2007 02  694.
 2007 03  22112.
 2007 04  51143·
 2007 05  56136·
 2007 06  76126.
 2007 07  28132·
 2007 08  35108.
 2007 09  74115.
 2007 10  55139.
 2007 11  21162.
 2007 12  79165·
 2008 01 45145·
 2008 02 24121.
 2008 03 14106·
 2008 04 2794·
 2008 05 4495.
 2008 06 92112.
 2008 07 44148·
 2008 08 47152·
 2008 09 71160.
 2008 10 89141·
 2008 11 75109·
 2008 12 34118.
 2009 01  5285.
 2009 02  72103.
 2009 03  9482·
 2009 04  8106.
 2009 05  38130·
 2009 06  22125.
 2009 07  15172.
 2009 08  12134.
 2009 09  394·
 2009 10  4788.
 2009 11  7593·
 2009 12  1576.
 2010 01 4891·
 2010 02 77113·
 2010 03 36108.
 2010 04 12133.
 2010 05 98117.
 2010 06 70102.
 2010 07 88126·
 2010 08 22126.
 2010 09 5116.
 2010 10 8113.
 2010 11 43111.
 2010 12 88114·
 2011 01  42103.
 2011 02  96144.
 2011 03  38145.
 2011 04  81119·
 2011 05  11107·
 2011 06  66120.
 2011 07  37153·
 2011 08  94128.
 2011 09  37122·
 2011 10  76118.
 2011 11  28111.
 2011 12  4678·
 2012 01 70125·
 2012 02 6126·
 2012 03 23100·
 2012 04 81113.
 2012 05 87106.
 2012 06 64142.
 2012 07 60136·
 2012 08 69153·
 2012 09 86165.
 2012 10 81164·
 2012 11 2153·
 2012 12 4145.
 2013 01  93124·
 2013 02  13116.
 2013 03  38111·
 2013 04  4132.
 2013 05  60133.
 2013 06  43176.
 2013 07  80155·
 2013 08  15148·
 2013 09  61103·
 2013 10  7697·
 2013 11  65101.
 2013 12  4140·
 2014 01 97104.
 2014 02 46130.
 2014 03 57134·
 2014 04 67130·
 2014 05 93175·
 2014 06 7199·
 2014 07 44175.
 2014 08 23167·
 2014 09 99122.
 2014 10 42131.
 2014 11 39137·
 2014 12 15151·
 2015 01  91144·
 2015 02  58128·
 2015 03  78163·
 2015 04  12125.
 2015 05  69140.
 2015 06  86165.
 2015 07  27206.
 2015 08  10186·
 2015 09  59160·
 2015 10  83140.
 2015 11  71153.
 2015 12  26147·
 2016 01 11111·
 2016 02 30100·
 2016 03 25132.
 2016 04 5149.
 2016 05 1143.
 2016 06 34197·
 2016 07 25173.
 2016 08 17152.
 2016 09 28183.
 2016 10 27145·
 2016 11 36156·
 2016 12 55192·
 2017 01  19163·
 2017 02  65153.
 2017 03  44127.
 2017 04  39144.
 2017 05  23143.
 2017 06  30155·
 2017 07  63190.
 2017 08  13192.
 2017 09  16204.
 2017 10  29193.
 2017 11  30188.


 2017 12  45189.
 2018 01 98205.
 2018 02 93197.
 2018 03 9177.
 2018 04 30192.
 2018 05 96177·
 2018 06 79155·
 2018 07 87164·
 2018 08 87119·
 2018 09 58116.
 2018 10 69117.
 2018 11 78139·
 2018 12 61157·
 2019 01  61138.
 2019 02  69131.
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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: Pvt W/S Workers, Retail trade Industry, Asian, 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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