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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 71871.
 1994 02 93916.
 1994 03 221005.
 1994 04 90922.
 1994 05 581003·
 1994 06 831010·
 1994 07 301057.
 1994 08 901093·
 1994 09 361018·
 1994 10 971079.
 1994 11 651025·
 1994 12 131028.
 1995 01  55955.
 1995 02  16929·
 1995 03  38968·
 1995 04  51019.
 1995 05  92994·
 1995 06  471161.
 1995 07  881246·
 1995 08  331195·
 1995 09  461043·
 1995 10  211074.
 1995 11  78955.
 1995 12  92989.
 1996 01 43960·
 1996 02 951019.
 1996 03 95939·
 1996 04 1938.
 1996 05 341040·
 1996 06 511108·
 1996 07 531238.
 1996 08 51097.
 1996 09 931021.
 1996 10 951022·
 1996 11 891067.
 1996 12 731034.
 1997 01  21994·
 1997 02  59997·
 1997 03  66998·
 1997 04  98995·
 1997 05  441179·
 1997 06  01196·
 1997 07  721225·
 1997 08  991068.
 1997 09  111000.
 1997 10  991032·
 1997 11  201066.
 1997 12  221048.
 1998 01 99854·
 1998 02 63941.
 1998 03 47926·
 1998 04 35966.
 1998 05 71026.
 1998 06 231056.
 1998 07 181035·
 1998 08 321076.
 1998 09 621003·
 1998 10 361060.
 1998 11 191179·
 1998 12 321073·
 1999 01  131050·
 1999 02  851146·
 1999 03  63976.
 1999 04  80877.
 1999 05  351038.
 1999 06  741122.
 1999 07  891180·
 1999 08  441056·
 1999 09  30968.
 1999 10  371056.
 1999 11  591067·
 1999 12  201040·
 2000 01 23981.
 2000 02 30996.
 2000 03 62963.
 2000 04 25987.
 2000 05 631021·
 2000 06 331098.
 2000 07 91098·
 2000 08 4986.
 2000 09 27939.
 2000 10 55946.
 2000 11 39937.
 2000 12 261028·
 2001 01  14893·
 2001 02  27964.
 2001 03  15888·
 2001 04  86958·
 2001 05  51972·
 2001 06  51001·
 2001 07  251109.
 2001 08  2926.
 2001 09  87982·
 2001 10  70933·
 2001 11  82887.
 2001 12  19887.
 2002 01 98831.
 2002 02 30800·
 2002 03 23945·
 2002 04 6932.
 2002 05 85968.
 2002 06 171031·
 2002 07 11981.
 2002 08 56865.
 2002 09 72903.
 2002 10 86926.
 2002 11 35896.
 2002 12 90963·
 2003 01  10848.
 2003 02  20905.
 2003 03  7959·
 2003 04  50948·
 2003 05  75911·
 2003 06  25961·
 2003 07  64986.
 2003 08  7965·
 2003 09  67841.
 2003 10  33856.
 2003 11  71885.
 2003 12  55823·
 2004 01 11842.
 2004 02 0872.
 2004 03 15899·
 2004 04 12935.
 2004 05 58923·
 2004 06 8962·
 2004 07 81085·
 2004 08 231026·
 2004 09 82981.
 2004 10 641049·
 2004 11 89991.
 2004 12 56997.
 2005 01  85869·
 2005 02  99927·
 2005 03  21905.
 2005 04  7950·
 2005 05  92878.
 2005 06  701153.
 2005 07  911166.
 2005 08  941092·
 2005 09  54986·
 2005 10  58991·
 2005 11  12979.
 2005 12  61955·
 2006 01 45957·
 2006 02 71892·
 2006 03 23910.
 2006 04 78951.
 2006 05 65947·
 2006 06 401055·
 2006 07 851048.
 2006 08 38911·
 2006 09 42969.
 2006 10 22918·
 2006 11 88960·
 2006 12 611033.
 2007 01  24865·
 2007 02  97935.
 2007 03  43928·
 2007 04  91931.
 2007 05  87963.
 2007 06  741079.
 2007 07  891063.
 2007 08  97896·
 2007 09  32871.
 2007 10  82987·
 2007 11  89941.
 2007 12  73964.
 2008 01 83904.
 2008 02 80889·
 2008 03 31894.
 2008 04 381000·
 2008 05 931038·
 2008 06 491116·
 2008 07 261135·
 2008 08 371097.
 2008 09 34929·
 2008 10 951006.
 2008 11 14939.
 2008 12 38927·
 2009 01  9847·
 2009 02  50868.
 2009 03  58872·
 2009 04  36865.
 2009 05  43839·
 2009 06  71958·
 2009 07  44956·
 2009 08  50827.
 2009 09  85884·
 2009 10  39919·
 2009 11  86942·
 2009 12  23904·
 2010 01 12787.
 2010 02 60874·
 2010 03 23948.
 2010 04 26885.
 2010 05 24972.
 2010 06 68936·
 2010 07 16934.
 2010 08 53970·
 2010 09 45837·
 2010 10 18869·
 2010 11 53869.
 2010 12 21856·
 2011 01  27844·
 2011 02  91950.
 2011 03  49890.
 2011 04  76939·
 2011 05  45981·
 2011 06  951001·
 2011 07  39934·
 2011 08  87960·
 2011 09  99916·
 2011 10  61951.
 2011 11  88925·
 2011 12  48972·
 2012 01 15887.
 2012 02 46878·
 2012 03 83900·
 2012 04 78879.
 2012 05 43910·
 2012 06 32902.
 2012 07 38951·
 2012 08 20891·
 2012 09 58943·
 2012 10 24854.
 2012 11 89986·
 2012 12 451028·
 2013 01  61926·
 2013 02  561031·
 2013 03  0925·
 2013 04  47930·
 2013 05  781007·
 2013 06  821113.
 2013 07  591089·
 2013 08  44965·
 2013 09  571049·
 2013 10  861030.
 2013 11  79930.
 2013 12  81943·
 2014 01 76940·
 2014 02 73951.
 2014 03 97963.
 2014 04 261040.
 2014 05 351068.
 2014 06 751096·
 2014 07 771094·
 2014 08 741037·
 2014 09 581063·
 2014 10 491152.
 2014 11 61042·
 2014 12 451004.
 2015 01  961002·
 2015 02  77995·
 2015 03  97983.
 2015 04  82989·
 2015 05  25974.
 2015 06  651114·
 2015 07  891096.
 2015 08  541025.
 2015 09  451009.
 2015 10  451081·
 2015 11  431026·
 2015 12  561027.
 2016 01 811023.
 2016 02 731096.
 2016 03 481097.
 2016 04 61060.
 2016 05 831115.
 2016 06 321018.
 2016 07 181120·
 2016 08 491130.
 2016 09 281061·
 2016 10 271125·
 2016 11 881150.
 2016 12 541069.
 2017 01  161116.
 2017 02  911150·
 2017 03  241275·
 2017 04  151085·
 2017 05  711101·
 2017 06  791175.


 2017 07  121214.
 2017 08  521156.
 2017 09  451118.
 2017 10  741008·
 2017 11  651054.
 2017 12  81025.
 2018 01 121105·
 2018 02 831242·
 2018 03 211268·
 2018 04 521140·
 2018 05 741119.
 2018 06 371168·
 2018 07 441153·
 2018 08 791179·
 2018 09 541172·
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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

New data set: Quarterly Financial Reporting: Manufacturing, Mining, Trade, and Selected Service Industries

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