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 Series Title: Employed: Nondurable goods manufacturing, Asian: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Yearly Chart  |  Excel file  |  Self-updating Excel file
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 2000 01 21295·
 2000 02 0311·
 2000 03 44299.
 2000 04 74294.
 2000 05 37291.
 2000 06 79348.
 2000 07 51372·
 2000 08 31311.
 2000 09 82307.
 2000 10 19306·
 2000 11 21308.
 2000 12 50297.
 2001 01  6310·
 2001 02  2290.
 2001 03  68277·
 2001 04  74275.
 2001 05  84288·
 2001 06  34323.
 2001 07  29365·
 2001 08  72323.
 2001 09  18320·
 2001 10  47338.
 2001 11  67394·
 2001 12  39363.
 2002 01 32332·
 2002 02 98314.
 2002 03 70271.
 2002 04 94287.
 2002 05 77284.
 2002 06 67374·
 2002 07 50342.
 2002 08 80385.
 2002 09 28374·
 2002 10 63306.
 2002 11 47321·
 2002 12 67288·
 2003 01  86285.
 2003 02  16289.
 2003 03  22295·
 2003 04  50316·
 2003 05  76301·
 2003 06  83309.
 2003 07  64308·
 2003 08  47337.
 2003 09  48334·
 2003 10  46288.
 2003 11  85284.
 2003 12  2257·
 2004 01 78258·
 2004 02 11309·
 2004 03 23332.
 2004 04 85278·
 2004 05 65281.
 2004 06 10272.
 2004 07 42272·
 2004 08 90272·
 2004 09 37274·
 2004 10 0294·
 2004 11 29252.
 2004 12 35291·
 2005 01  42262.
 2005 02  62226·
 2005 03  97234·
 2005 04  66211.
 2005 05  57207.
 2005 06  3264.
 2005 07  83233.
 2005 08  50249.
 2005 09  81234.
 2005 10  54269·
 2005 11  52263.
 2005 12  83253·
 2006 01 41234·
 2006 02 73211.
 2006 03 90276·
 2006 04 83243·
 2006 05 85285.
 2006 06 41291.
 2006 07 10238.
 2006 08 95234·
 2006 09 91237.
 2006 10 64253·
 2006 11 51215·
 2006 12 88226·
 2007 01  58297·
 2007 02  75259·
 2007 03  76281·
 2007 04  55279·
 2007 05  12249·
 2007 06  29283.
 2007 07  71303.
 2007 08  16289·
 2007 09  3326·
 2007 10  8283.
 2007 11  51281.
 2007 12  16313·
 2008 01 6259·
 2008 02 20313·
 2008 03 53318.
 2008 04 22274.
 2008 05 22319.
 2008 06 95354·
 2008 07 39356.
 2008 08 31331·
 2008 09 76289·
 2008 10 91287.
 2008 11 99247·
 2008 12 59214·
 2009 01  19222.
 2009 02  88217.
 2009 03  44242·
 2009 04  52276·
 2009 05  26279·
 2009 06  95344.
 2009 07  12313·
 2009 08  80315·
 2009 09  97316.
 2009 10  41239.
 2009 11  67214·
 2009 12  35190·
 2010 01 58182.
 2010 02 85222·
 2010 03 97248·
 2010 04 37275.
 2010 05 59288.
 2010 06 7237.
 2010 07 14242·
 2010 08 30279·
 2010 09 76298·
 2010 10 14336.
 2010 11 55327.
 2010 12 84289·
 2011 01  8283·
 2011 02  38294·
 2011 03  85275·
 2011 04  92253.
 2011 05  82259·
 2011 06  35215.
 2011 07  91249.
 2011 08  74252.
 2011 09  48310.
 2011 10  88323.
 2011 11  86298·
 2011 12  74300.
 2012 01 81279·
 2012 02 2269·
 2012 03 7271.
 2012 04 61325·
 2012 05 81331·
 2012 06 10321·
 2012 07 18327.
 2012 08 29290.
 2012 09 74280.
 2012 10 68285·
 2012 11 6289·
 2012 12 97314.
 2013 01  11281.
 2013 02  57326.
 2013 03  84311.
 2013 04  9312.
 2013 05  66375·
 2013 06  85387·
 2013 07  91371·
 2013 08  35373.
 2013 09  40372.
 2013 10  82303.
 2013 11  89338·
 2013 12  69320.
 2014 01 59309·
 2014 02 7302.
 2014 03 66331.
 2014 04 29345.
 2014 05 73339·
 2014 06 39346·
 2014 07 35349.
 2014 08 60387·
 2014 09 57405.
 2014 10 87389.
 2014 11 34282.
 2014 12 32295.
 2015 01  11328·
 2015 02  81351·
 2015 03  26364·
 2015 04  37332·
 2015 05  62338·
 2015 06  78333·
 2015 07  98294·
 2015 08  96328·
 2015 09  59341·
 2015 10  59342·
 2015 11  64344·
 2015 12  53381·
 2016 01 77375·
 2016 02 33354.
 2016 03 60335.
 2016 04 76332.
 2016 05 18302·
 2016 06 29289.
 2016 07 52312.
 2016 08 60333.
 2016 09 7412.
 2016 10 5425·
 2016 11 25398.
 2016 12 23363·
 2017 01  93318·
 2017 02  43396.
 2017 03  94352.
 2017 04  11374·
 2017 05  53391.
 2017 06  48392·
 2017 07  95344.
 2017 08  92405.


 2017 09  87370·
 2017 10  53370.
 2017 11  92336.
 2017 12  60398·
 2018 01 20370.
 2018 02 14336·
 2018 03 73306.
 2018 04 35323·
 2018 05 2357·
 2018 06 14387.
 2018 07 51316·
 2018 08 61394.
 2018 09 9336·
 2018 10 58295.
 2018 11 63324.
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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: Employed: Nondurable goods manufacturing, Asian: 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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