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 Series Title: Employment Level: Never Married Multiple Jobholders Men: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Yearly Chart  |  Excel file  |  Self-updating Excel file
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 1994 01 92871.
 1994 02 38916.
 1994 03 881005.
 1994 04 61922·
 1994 05 41003.
 1994 06 651010·
 1994 07 921057.
 1994 08 661093·
 1994 09 461018.
 1994 10 521079·
 1994 11 591025.
 1994 12 311028·
 1995 01  67955.
 1995 02  81929.
 1995 03  3968·
 1995 04  21019.
 1995 05  43994·
 1995 06  601161.
 1995 07  601246.
 1995 08  471195·
 1995 09  731043·
 1995 10  201074·
 1995 11  95955·
 1995 12  61989.
 1996 01 84960.
 1996 02 181019·
 1996 03 95939·
 1996 04 62938.
 1996 05 261040.
 1996 06 341108.
 1996 07 731238·
 1996 08 951097.
 1996 09 741021.
 1996 10 771022.
 1996 11 661067.
 1996 12 301034.
 1997 01  29994.
 1997 02  76997.
 1997 03  38998·
 1997 04  59995·
 1997 05  151179·
 1997 06  901196·
 1997 07  771225.
 1997 08  31068.
 1997 09  841000.
 1997 10  01032·
 1997 11  951066.
 1997 12  51048.
 1998 01 11854.
 1998 02 12941.
 1998 03 30926·
 1998 04 35966·
 1998 05 961026.
 1998 06 581056·
 1998 07 461035.
 1998 08 861076.
 1998 09 641003.
 1998 10 951060.
 1998 11 291179.
 1998 12 791073.
 1999 01  661050.
 1999 02  41146·
 1999 03  94976.
 1999 04  56877·
 1999 05  781038·
 1999 06  921122.
 1999 07  771180·
 1999 08  871056.
 1999 09  99968·
 1999 10  901056.
 1999 11  431067.
 1999 12  671040·
 2000 01 55981·
 2000 02 56996·
 2000 03 78963.
 2000 04 14987.
 2000 05 971021·
 2000 06 701098.
 2000 07 951098.
 2000 08 73986.
 2000 09 0939·
 2000 10 41946.
 2000 11 33937.
 2000 12 121028.
 2001 01  64893·
 2001 02  98964·
 2001 03  54888·
 2001 04  27958·
 2001 05  14972·
 2001 06  991001.
 2001 07  471109·
 2001 08  35926·
 2001 09  2982.
 2001 10  25933.
 2001 11  23887.
 2001 12  81887·
 2002 01 2831·
 2002 02 84800.
 2002 03 22945·
 2002 04 35932·
 2002 05 15968.
 2002 06 61031.
 2002 07 5981.
 2002 08 90865·
 2002 09 66903.
 2002 10 48926·
 2002 11 62896·
 2002 12 65963.
 2003 01  5848.
 2003 02  93905.
 2003 03  4959·
 2003 04  5948·
 2003 05  9911·
 2003 06  46961.
 2003 07  69986.
 2003 08  79965·
 2003 09  77841·
 2003 10  39856.
 2003 11  21885·
 2003 12  81823·
 2004 01 35842·
 2004 02 30872.
 2004 03 47899·
 2004 04 30935.
 2004 05 33923·
 2004 06 99962·
 2004 07 611085.
 2004 08 711026.
 2004 09 47981.
 2004 10 531049·
 2004 11 0991.
 2004 12 71997.
 2005 01  76869·
 2005 02  24927·
 2005 03  26905.
 2005 04  27950·
 2005 05  47878.
 2005 06  681153.
 2005 07  291166·
 2005 08  551092.
 2005 09  9986·
 2005 10  67991.
 2005 11  20979·
 2005 12  2955.
 2006 01 39957·
 2006 02 29892·
 2006 03 39910·
 2006 04 36951.
 2006 05 36947·
 2006 06 831055.
 2006 07 461048·
 2006 08 50911·
 2006 09 27969.
 2006 10 88918.
 2006 11 31960·
 2006 12 651033·
 2007 01  60865.
 2007 02  24935·
 2007 03  7928·
 2007 04  25931·
 2007 05  12963.
 2007 06  991079·
 2007 07  111063·
 2007 08  97896·
 2007 09  83871·
 2007 10  43987.
 2007 11  6941.
 2007 12  78964.
 2008 01 99904·
 2008 02 14889·
 2008 03 79894·
 2008 04 851000.
 2008 05 91038.
 2008 06 941116·
 2008 07 451135·
 2008 08 631097.
 2008 09 90929·
 2008 10 881006·
 2008 11 41939.
 2008 12 82927.
 2009 01  41847·
 2009 02  29868.
 2009 03  29872.
 2009 04  34865.
 2009 05  89839.
 2009 06  73958·
 2009 07  98956.
 2009 08  40827.
 2009 09  83884·
 2009 10  1919·
 2009 11  61942·
 2009 12  43904.
 2010 01 98787.
 2010 02 21874.
 2010 03 55948·
 2010 04 13885.
 2010 05 36972.
 2010 06 65936.
 2010 07 43934.
 2010 08 44970.
 2010 09 21837·
 2010 10 88869.
 2010 11 13869·
 2010 12 54856.
 2011 01  5844·
 2011 02  72950·
 2011 03  79890·
 2011 04  89939.
 2011 05  62981·
 2011 06  241001·
 2011 07  77934·
 2011 08  17960·
 2011 09  92916·
 2011 10  76951.
 2011 11  71925·
 2011 12  32972.
 2012 01 22887·
 2012 02 84878·
 2012 03 49900·
 2012 04 54879·
 2012 05 1910.
 2012 06 31902·
 2012 07 23951·
 2012 08 26891.
 2012 09 5943.
 2012 10 21854·
 2012 11 32986.
 2012 12 181028·
 2013 01  35926·
 2013 02  881031·
 2013 03  38925·
 2013 04  24930.
 2013 05  151007.
 2013 06  881113·
 2013 07  301089·
 2013 08  63965.
 2013 09  961049·
 2013 10  21030.
 2013 11  20930·
 2013 12  79943.
 2014 01 54940.
 2014 02 38951·
 2014 03 46963·
 2014 04 421040·
 2014 05 891068.
 2014 06 261096·
 2014 07 711094.
 2014 08 451037·
 2014 09 251063·
 2014 10 231152.
 2014 11 821042·
 2014 12 71004.
 2015 01  151002·
 2015 02  12995.
 2015 03  94983·
 2015 04  73989.
 2015 05  33974.
 2015 06  981114.
 2015 07  431096.
 2015 08  131025.
 2015 09  791009·
 2015 10  141081·
 2015 11  921026.
 2015 12  191027·
 2016 01 791023.
 2016 02 151096.
 2016 03 301097.
 2016 04 111060·
 2016 05 831115.
 2016 06 841018.
 2016 07 691120.
 2016 08 341130·
 2016 09 671061.
 2016 10 281125·
 2016 11 481150·
 2016 12 561069·
 2017 01  311116·
 2017 02  771150.
 2017 03  281275.
 2017 04  721085.


 2017 05  01101.
 2017 06  891175·
 2017 07  991214.
 2017 08  01156.
 2017 09  251118.
 2017 10  451008·
 2017 11  721054.
 2017 12  851025·
 2018 01 811105.
 2018 02 521242·
 2018 03 861268.
 2018 04 971140·
 2018 05 691119.
 2018 06 411168·
 2018 07 41153·
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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: Never Married Multiple Jobholders Men: 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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