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 Series Title: Persons At Work in Durable Goods Manufacturing Industries, Wage and Salary Workers, Worked 1-34 Hours: 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 731142.
 2000 02 691061·
 2000 03 951074·
 2000 04 921083·
 2000 05 231080.
 2000 06 561231·
 2000 07 581151.
 2000 08 291203.
 2000 09 47993.
 2000 10 481292.
 2000 11 291271·
 2000 12 711218.
 2001 01  931277·
 2001 02  271381·
 2001 03  201234.
 2001 04  632308·
 2001 05  381102.
 2001 06  981271·
 2001 07  691157.
 2001 08  721159·
 2001 09  811248.
 2001 10  941324·
 2001 11  381352.
 2001 12  941181.
 2002 01 481089.
 2002 02 711232·
 2002 03 161137·
 2002 04 471029.
 2002 05 911071.
 2002 06 121015.
 2002 07 161053.
 2002 08 761133·
 2002 09 83903.
 2002 10 22983.
 2002 11 751159·
 2002 12 501190.
 2003 01  251022·
 2003 02  331212·
 2003 03  571043.
 2003 04  62902·
 2003 05  431002.
 2003 06  2952·
 2003 07  491033·
 2003 08  331297.
 2003 09  87956.
 2003 10  101162.
 2003 11  641049·
 2003 12  61017·
 2004 01 33869.
 2004 02 64905·
 2004 03 41911.
 2004 04 501092·
 2004 05 80997.
 2004 06 97979.
 2004 07 411020·
 2004 08 591000.
 2004 09 551108.
 2004 10 631013·
 2004 11 531084.
 2004 12 54984·
 2005 01  8910·
 2005 02  46970·
 2005 03  90895.
 2005 04  77942·
 2005 05  13870.
 2005 06  51893·
 2005 07  89952.
 2005 08  97959.
 2005 09  72813.
 2005 10  111052·
 2005 11  141001.
 2005 12  10982.
 2006 01 101034.
 2006 02 821058.
 2006 03 52973·
 2006 04 341654.
 2006 05 77867.
 2006 06 45891.
 2006 07 17892.
 2006 08 13988.
 2006 09 49864·
 2006 10 81077.
 2006 11 461018·
 2006 12 17975.
 2007 01  261022·
 2007 02  11360.
 2007 03  2977.
 2007 04  401076·
 2007 05  33855.
 2007 06  82784.
 2007 07  731001·
 2007 08  01031·
 2007 09  21871·
 2007 10  32978.
 2007 11  71912·
 2007 12  42909.
 2008 01 65874.
 2008 02 581079·
 2008 03 36943·
 2008 04 34956·
 2008 05 65906·
 2008 06 92968·
 2008 07 291070.
 2008 08 73907·
 2008 09 481055·
 2008 10 891130·
 2008 11 391340.
 2008 12 751107.
 2009 01  631205·
 2009 02  331286.
 2009 03  781182·
 2009 04  861298·
 2009 05  861244.
 2009 06  281245·
 2009 07  841144·
 2009 08  741216.
 2009 09  173144.
 2009 10  81186·
 2009 11  211186·
 2009 12  341051·
 2010 01 81917·
 2010 02 281152.
 2010 03 76851·
 2010 04 85828.
 2010 05 29869·
 2010 06 71891.
 2010 07 61945·
 2010 08 711027.
 2010 09 37916.
 2010 10 42989·
 2010 11 161055·
 2010 12 61951·
 2011 01  41241·
 2011 02  74950·
 2011 03  2884.
 2011 04  49854.
 2011 05  57858.
 2011 06  24895·
 2011 07  8945.
 2011 08  55932·
 2011 09  45944.
 2011 10  721017.
 2011 11  47997.
 2011 12  22868·
 2012 01 43862.
 2012 02 25935·
 2012 03 561013.
 2012 04 20913·
 2012 05 53799.
 2012 06 16792·
 2012 07 98833.
 2012 08 43959·
 2012 09 0886.
 2012 10 1993·
 2012 11 62933·
 2012 12 10843.
 2013 01  34885.
 2013 02  61918.
 2013 03  60834.
 2013 04  65750.
 2013 05  30692·
 2013 06  3802.
 2013 07  29910·
 2013 08  77956.
 2013 09  89853·
 2013 10  59810·
 2013 11  34848.
 2013 12  41957.
 2014 01 36785.
 2014 02 851217.
 2014 03 61822.
 2014 04 75836·
 2014 05 22748.
 2014 06 63787·
 2014 07 24961·
 2014 08 231039·
 2014 09 21812·
 2014 10 01002.
 2014 11 61960·
 2014 12 56819·
 2015 01  36853·
 2015 02  27964·
 2015 03  34906·
 2015 04  67760·
 2015 05  90790·
 2015 06  1840.
 2015 07  31873.
 2015 08  74825.
 2015 09  343083.
 2015 10  31100.
 2015 11  66981·
 2015 12  23815·
 2016 01 43870·
 2016 02 41856.
 2016 03 76865.
 2016 04 82784.
 2016 05 19773.
 2016 06 45839·
 2016 07 24912.
 2016 08 46933.
 2016 09 86922.
 2016 10 731112.
 2016 11 971199.
 2016 12 341006.
 2017 01  95968.
 2017 02  6953·


 2017 03  101090.
 2017 04  891450·
 2017 05  20797·
 2017 06  51823.
 2017 07  99829.
 2017 08  81791·
 2017 09  64876.
 2017 10  39858.
 2017 11  28923.
 2017 12  4888.
 2018 01 50891.
 2018 02 271001.
 2018 03 84885·
 2018 04 78769.
 2018 05 29710·
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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: Persons At Work in Durable Goods Manufacturing Industries, Wage and Salary Workers, Worked 1-34 Hours: 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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