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 Series Title: Employed: Wage and salary workers, Durable goods manufacturing: 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 5212490.
 2000 02 3512471·
 2000 03 9312608.
 2000 04 9312643·
 2000 05 2212421.
 2000 06 7312336·
 2000 07 3912032·
 2000 08 4312096.
 2000 09 8912009.
 2000 10 4012126·
 2000 11 1612147.
 2000 12 2312201.
 2001 01  511990.
 2001 02  1911920·
 2001 03  3811936·
 2001 04  7711857.
 2001 05  4411749·
 2001 06  1611582·
 2001 07  4411356.
 2001 08  7411147·
 2001 09  611088·
 2001 10  6211174·
 2001 11  9510897.
 2001 12  910981.
 2002 01 1810737·
 2002 02 1510751·
 2002 03 8010908.
 2002 04 010699·
 2002 05 2910682.
 2002 06 5610446.
 2002 07 1110511·
 2002 08 9210484.
 2002 09 1510420.
 2002 10 9110733.
 2002 11 2710582·
 2002 12 5410739·
 2003 01  7710702.
 2003 02  5210713.
 2003 03  9010306.
 2003 04  7910262.
 2003 05  3910218.
 2003 06  9710239.
 2003 07  8910034.
 2003 08  8810190.
 2003 09  5210091·
 2003 10  610232.
 2003 11  3610424·
 2003 12  2310427·
 2004 01 9210191·
 2004 02 8510187.
 2004 03 699931·
 2004 04 5510086.
 2004 05 5910065.
 2004 06 6810041.
 2004 07 5110047·
 2004 08 7810296.
 2004 09 7810147·
 2004 10 1010069.
 2004 11 6910099.
 2004 12 1010279·
 2005 01  9910248.
 2005 02  939997.
 2005 03  3810108·
 2005 04  9610138.
 2005 05  999985.
 2005 06  2410178.
 2005 07  949969.
 2005 08  59810.
 2005 09  7710084·
 2005 10  3410136.
 2005 11  010264.
 2005 12  3010511.
 2006 01 5910507.
 2006 02 8010470.
 2006 03 4510673.
 2006 04 9210392.
 2006 05 9510278.
 2006 06 4410374·
 2006 07 4210262.
 2006 08 3410074·
 2006 09 6110189·
 2006 10 3210178.
 2006 11 279895·
 2006 12 2610166·
 2007 01  579854·
 2007 02  7610229.
 2007 03  6510233·
 2007 04  6110142.
 2007 05  810317.
 2007 06  3210003.
 2007 07  4210050·
 2007 08  5910037.
 2007 09  6510050.
 2007 10  8310214·
 2007 11  7310360·
 2007 12  6410262·
 2008 01 410077·
 2008 02 3410016·
 2008 03 9410070·
 2008 04 4510198·
 2008 05 2310023.
 2008 06 1810316·
 2008 07 6910176·
 2008 08 9610147·
 2008 09 5010087.
 2008 10 919999·
 2008 11 8510058.
 2008 12 369729.
 2009 01  349261.
 2009 02  349115.
 2009 03  568731·
 2009 04  108766.
 2009 05  518765.
 2009 06  558620·
 2009 07  198758·
 2009 08  868756·
 2009 09  18630·
 2009 10  858636.
 2009 11  378474.
 2009 12  598198·
 2010 01 108108·
 2010 02 818197·
 2010 03 988246.
 2010 04 488489·
 2010 05 278666.
 2010 06 248714.
 2010 07 168953·
 2010 08 968913·
 2010 09 298782·
 2010 10 218728.
 2010 11 278654.
 2010 12 748740.
 2011 01  158748.
 2011 02  38556.
 2011 03  958711·
 2011 04  768801·
 2011 05  128725.
 2011 06  288960.
 2011 07  88844·
 2011 08  198800.
 2011 09  699074.
 2011 10  778840.
 2011 11  788808.
 2011 12  499094·
 2012 01 628869.
 2012 02 568968.
 2012 03 448862.
 2012 04 358965.
 2012 05 918929·
 2012 06 979076.
 2012 07 689160.
 2012 08 719104.
 2012 09 829242.
 2012 10 579259·
 2012 11 389219.
 2012 12 769020.
 2013 01  858980.
 2013 02  178999·
 2013 03  679028.
 2013 04  938959·
 2013 05  759022.
 2013 06  859091·
 2013 07  939306.
 2013 08  939474·
 2013 09  539513·
 2013 10  919447.
 2013 11  809477.
 2013 12  709369·
 2014 01 449453·
 2014 02 939386.
 2014 03 149180·
 2014 04 429217.
 2014 05 999492.
 2014 06 719546·
 2014 07 89438·
 2014 08 549566·
 2014 09 939256·
 2014 10 339235·
 2014 11 29176.
 2014 12 749375.
 2015 01  269469.
 2015 02  119422·
 2015 03  569388.
 2015 04  989371.
 2015 05  259538·
 2015 06  609600.
 2015 07  609859·
 2015 08  439688·
 2015 09  389570.
 2015 10  639732·
 2015 11  279453.
 2015 12  559359·
 2016 01 429360.
 2016 02 269250.
 2016 03 939553·
 2016 04 29586.
 2016 05 369480·
 2016 06 819512·
 2016 07 229542.
 2016 08 799531·
 2016 09 479704.
 2016 10 849725.
 2016 11 39660·
 2016 12 49590.
 2017 01  259249·
 2017 02  179451.
 2017 03  479567.
 2017 04  229726.
 2017 05  459793.


 2017 06  889642.
 2017 07  939697·
 2017 08  29265·
 2017 09  89338.
 2017 10  269515.
 2017 11  39590.
 2017 12  399471·
 2018 01 389451.
 2018 02 909520.
 2018 03 669588.
 2018 04 509688·
 2018 05 879667·
 2018 06 609416·
 2018 07 949514·
 2018 08 819558.
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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, Durable goods manufacturing: 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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