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 Series Title: Employed: Wage and salary workers, Nondurable goods manufacturing, Women: NSA
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 2000 01 652672·
 2000 02 482812·
 2000 03 22735·
 2000 04 812635·
 2000 05 612675·
 2000 06 212802·
 2000 07 422780·
 2000 08 362699·
 2000 09 922628.
 2000 10 622487·
 2000 11 522518.
 2000 12 582648.
 2001 01  92593·
 2001 02  512668.
 2001 03  452607.
 2001 04  912444·
 2001 05  872487·
 2001 06  962380·
 2001 07  582359.
 2001 08  62378.
 2001 09  262277·
 2001 10  292291·
 2001 11  542344.
 2001 12  952357·
 2002 01 512375.
 2002 02 52393.
 2002 03 212306.
 2002 04 782259·
 2002 05 142249.
 2002 06 62300·
 2002 07 732304.
 2002 08 992437.
 2002 09 892294·
 2002 10 402233·
 2002 11 472291.
 2002 12 282195.
 2003 01  772294.
 2003 02  372251·
 2003 03  52240·
 2003 04  582304·
 2003 05  32177·
 2003 06  542233·
 2003 07  362258·
 2003 08  82345·
 2003 09  172227.
 2003 10  742289.
 2003 11  532271.
 2003 12  242154.
 2004 01 962263·
 2004 02 22265·
 2004 03 942282.
 2004 04 732216.
 2004 05 392342·
 2004 06 702225.
 2004 07 212174.
 2004 08 502210·
 2004 09 722153.
 2004 10 362134.
 2004 11 222175.
 2004 12 742181·
 2005 01  452109·
 2005 02  802180·
 2005 03  112104·
 2005 04  892195·
 2005 05  342188.
 2005 06  92188.
 2005 07  242158.
 2005 08  652149·
 2005 09  382096·
 2005 10  542046.
 2005 11  262026.
 2005 12  952010·
 2006 01 842101·
 2006 02 742113.
 2006 03 42134.
 2006 04 992046.
 2006 05 222099.
 2006 06 482146.
 2006 07 702074.
 2006 08 202087·
 2006 09 262019·
 2006 10 842010.
 2006 11 632008·
 2006 12 291941·
 2007 01  992129·
 2007 02  142078.
 2007 03  462111.
 2007 04  192043·
 2007 05  642009·
 2007 06  942098.
 2007 07  62180.
 2007 08  92191·
 2007 09  722151·
 2007 10  52131.
 2007 11  562071·
 2007 12  432107.
 2008 01 992093.
 2008 02 542020.
 2008 03 352019.
 2008 04 911955.
 2008 05 452018·
 2008 06 742011.
 2008 07 52056·
 2008 08 462062.
 2008 09 361951·
 2008 10 201915·
 2008 11 541843.
 2008 12 291587·
 2009 01  211603·
 2009 02  751697.
 2009 03  951745·
 2009 04  821864.
 2009 05  771912·
 2009 06  441930.
 2009 07  661932.
 2009 08  751901·
 2009 09  41891·
 2009 10  601779.
 2009 11  291704.
 2009 12  21639.
 2010 01 261644·
 2010 02 781693·
 2010 03 731726·
 2010 04 831765·
 2010 05 951805·
 2010 06 821825·
 2010 07 111742·
 2010 08 611725·
 2010 09 851760.
 2010 10 771734·
 2010 11 791791·
 2010 12 61815.
 2011 01  981715·
 2011 02  961835.
 2011 03  431815·
 2011 04  121787.
 2011 05  591719·
 2011 06  941769.
 2011 07  881778·
 2011 08  981846.
 2011 09  171861.
 2011 10  531971·
 2011 11  281963·
 2011 12  71870·
 2012 01 491787·
 2012 02 801796.
 2012 03 11885·
 2012 04 101887.
 2012 05 541935.
 2012 06 71927·
 2012 07 711934.
 2012 08 01938.
 2012 09 591848.
 2012 10 901921·
 2012 11 231840.
 2012 12 971844·
 2013 01  131844.
 2013 02  111806·
 2013 03  731889.
 2013 04  441914·
 2013 05  921993·
 2013 06  772003.
 2013 07  571945.
 2013 08  111940.
 2013 09  971953·
 2013 10  191820·
 2013 11  381898·
 2013 12  921852.
 2014 01 521894·
 2014 02 941938·
 2014 03 51940.
 2014 04 61863.
 2014 05 81961.
 2014 06 831969.
 2014 07 691975·
 2014 08 982048·
 2014 09 412045.
 2014 10 932028.
 2014 11 701944·
 2014 12 351876.
 2015 01  511996.
 2015 02  572021·
 2015 03  701954.
 2015 04  131952.
 2015 05  631888.
 2015 06  291974.
 2015 07  572082.
 2015 08  502095.
 2015 09  272083.
 2015 10  932055.
 2015 11  431999.
 2015 12  921992·
 2016 01 202013·
 2016 02 541943·
 2016 03 671997.
 2016 04 61856·
 2016 05 411858.
 2016 06 451826·
 2016 07 921917·
 2016 08 872050·
 2016 09 162057·
 2016 10 212132.
 2016 11 52100·
 2016 12 542038.
 2017 01  952006.
 2017 02  652013·
 2017 03  192032·
 2017 04  522073.
 2017 05  541962.


 2017 06  841958.
 2017 07  721918·
 2017 08  491968·
 2017 09  932077.
 2017 10  82061·
 2017 11  282092.
 2017 12  401993.
 2018 01 371934·
 2018 02 952015·
 2018 03 742012·
 2018 04 432012.
 2018 05 372006.
 2018 06 262081·
 2018 07 221985.
 2018 08 41959.
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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: Wage and salary workers, Nondurable goods manufacturing, Women: 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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