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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 68871.
 1994 02 6916.
 1994 03 951005.
 1994 04 68922·
 1994 05 841003·
 1994 06 11010·
 1994 07 841057.
 1994 08 231093.
 1994 09 911018.
 1994 10 201079.
 1994 11 981025·
 1994 12 11028·
 1995 01  41955·
 1995 02  44929.
 1995 03  51968.
 1995 04  471019.
 1995 05  7994·
 1995 06  791161.
 1995 07  811246.
 1995 08  301195.
 1995 09  911043·
 1995 10  581074·
 1995 11  50955·
 1995 12  44989·
 1996 01 18960.
 1996 02 371019·
 1996 03 47939·
 1996 04 8938·
 1996 05 381040.
 1996 06 971108·
 1996 07 851238·
 1996 08 661097.
 1996 09 271021.
 1996 10 461022·
 1996 11 01067·
 1996 12 881034·
 1997 01  85994·
 1997 02  15997·
 1997 03  57998·
 1997 04  68995·
 1997 05  371179·
 1997 06  601196·
 1997 07  421225·
 1997 08  241068.
 1997 09  341000·
 1997 10  641032·
 1997 11  701066.
 1997 12  21048·
 1998 01 52854·
 1998 02 32941.
 1998 03 77926.
 1998 04 69966.
 1998 05 901026.
 1998 06 971056.
 1998 07 271035.
 1998 08 211076·
 1998 09 741003·
 1998 10 151060.
 1998 11 81179·
 1998 12 761073·
 1999 01  541050·
 1999 02  681146·
 1999 03  32976·
 1999 04  78877·
 1999 05  71038·
 1999 06  631122.
 1999 07  381180·
 1999 08  981056·
 1999 09  31968.
 1999 10  301056.
 1999 11  881067·
 1999 12  271040.
 2000 01 53981·
 2000 02 27996·
 2000 03 70963·
 2000 04 87987.
 2000 05 241021.
 2000 06 361098·
 2000 07 971098·
 2000 08 21986·
 2000 09 17939.
 2000 10 62946.
 2000 11 7937·
 2000 12 981028·
 2001 01  34893·
 2001 02  38964.
 2001 03  63888·
 2001 04  13958.
 2001 05  1972·
 2001 06  211001·
 2001 07  521109·
 2001 08  84926.
 2001 09  67982.
 2001 10  91933.
 2001 11  88887·
 2001 12  55887·
 2002 01 7831·
 2002 02 56800.
 2002 03 9945.
 2002 04 96932.
 2002 05 24968·
 2002 06 471031·
 2002 07 77981.
 2002 08 2865·
 2002 09 41903.
 2002 10 21926.
 2002 11 80896.
 2002 12 90963·
 2003 01  9848·
 2003 02  60905.
 2003 03  32959.
 2003 04  5948·
 2003 05  3911.
 2003 06  69961.
 2003 07  70986.
 2003 08  17965.
 2003 09  24841.
 2003 10  82856.
 2003 11  56885.
 2003 12  19823.
 2004 01 98842·
 2004 02 53872·
 2004 03 79899·
 2004 04 31935.
 2004 05 74923·
 2004 06 66962.
 2004 07 531085.
 2004 08 961026.
 2004 09 29981.
 2004 10 271049.
 2004 11 13991·
 2004 12 85997.
 2005 01  62869.
 2005 02  67927·
 2005 03  25905·
 2005 04  90950·
 2005 05  98878.
 2005 06  421153.
 2005 07  741166·
 2005 08  321092·
 2005 09  89986·
 2005 10  36991·
 2005 11  75979·
 2005 12  53955.
 2006 01 10957·
 2006 02 53892.
 2006 03 65910.
 2006 04 25951·
 2006 05 60947.
 2006 06 271055.
 2006 07 81048.
 2006 08 40911.
 2006 09 66969.
 2006 10 13918.
 2006 11 90960.
 2006 12 171033·
 2007 01  78865·
 2007 02  93935·
 2007 03  25928.
 2007 04  2931·
 2007 05  71963·
 2007 06  741079·
 2007 07  511063.
 2007 08  62896·
 2007 09  45871·
 2007 10  88987.
 2007 11  30941.
 2007 12  93964.
 2008 01 27904.
 2008 02 90889.
 2008 03 51894·
 2008 04 131000.
 2008 05 661038·
 2008 06 641116.
 2008 07 271135.
 2008 08 661097.
 2008 09 37929.
 2008 10 141006·
 2008 11 94939.
 2008 12 22927.
 2009 01  42847.
 2009 02  74868·
 2009 03  17872.
 2009 04  75865.
 2009 05  5839.
 2009 06  99958.
 2009 07  84956.
 2009 08  43827·
 2009 09  77884·
 2009 10  72919·
 2009 11  6942·
 2009 12  72904·
 2010 01 34787·
 2010 02 99874.
 2010 03 21948.
 2010 04 29885·
 2010 05 75972·
 2010 06 11936.
 2010 07 94934.
 2010 08 10970·
 2010 09 26837.
 2010 10 65869·
 2010 11 12869·
 2010 12 34856·
 2011 01  38844·
 2011 02  44950·
 2011 03  86890·
 2011 04  43939·
 2011 05  85981.
 2011 06  521001.
 2011 07  57934·
 2011 08  9960.
 2011 09  69916·
 2011 10  23951.
 2011 11  85925.
 2011 12  24972·
 2012 01 15887·
 2012 02 13878.
 2012 03 60900.
 2012 04 9879·
 2012 05 72910.
 2012 06 3902.
 2012 07 94951·
 2012 08 6891·
 2012 09 17943.
 2012 10 0854.
 2012 11 25986.
 2012 12 861028.
 2013 01  50926·
 2013 02  361031.
 2013 03  16925.
 2013 04  42930·
 2013 05  961007.
 2013 06  671113·
 2013 07  551089·
 2013 08  94965.
 2013 09  51049·
 2013 10  751030·
 2013 11  54930.
 2013 12  85943.
 2014 01 54940·
 2014 02 67951.
 2014 03 52963.
 2014 04 851040·
 2014 05 421068·
 2014 06 741096·
 2014 07 121094.
 2014 08 891037·
 2014 09 951063.
 2014 10 531152.
 2014 11 201042·
 2014 12 141004·
 2015 01  631002.
 2015 02  86995.
 2015 03  91983.
 2015 04  5989.
 2015 05  21974.
 2015 06  781114·
 2015 07  621096·
 2015 08  321025·
 2015 09  711009·
 2015 10  631081·
 2015 11  971026.
 2015 12  881027.
 2016 01 361023·
 2016 02 961096.
 2016 03 821097·
 2016 04 941060.
 2016 05 691115.
 2016 06 591018·
 2016 07 301120.
 2016 08 911130·
 2016 09 441061·
 2016 10 591125·
 2016 11 811150·
 2016 12 511069.
 2017 01  611116.
 2017 02  271150·


 2017 03  961275.
 2017 04  671085·
 2017 05  461101·
 2017 06  211175.
 2017 07  641214.
 2017 08  581156.
 2017 09  491118·
 2017 10  201008.
 2017 11  971054·
 2017 12  691025·
 2018 01 461105·
 2018 02 341242·
 2018 03 331268.
 2018 04 681140·
 2018 05 371119.
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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
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