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 Series Title: Employment Level: Nonagriculture, Unpaid Family Workers, 16-19 years, Men: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Yearly Chart  |  Excel file  |  Self-updating Excel file
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 1976 06 3630·
 1976 07 629·
 1976 08 4433·
 1976 09 9017·
 1976 10 918.
 1976 11 658.
 1976 12 3014.
 1977 01  9910·
 1977 02  5417·
 1977 03  2924·
 1977 04  2230.
 1977 05  1425·
 1977 06  2231·
 1977 07  8034.
 1977 08  3525·
 1977 09  7711.
 1977 10  8816·
 1977 11  2313·
 1977 12  515.
 1978 01 5820.
 1978 02 5422.
 1978 03 9126·
 1978 04 9718·
 1978 05 5224·
 1978 06 4326.
 1978 07 4030·
 1978 08 9732·
 1978 09 7710·
 1978 10 710·
 1978 11 5210.
 1978 12 1914·
 1979 01  7817.
 1979 02  2120.
 1979 03  3416·
 1979 04  024·
 1979 05  2325.
 1979 06  8525.
 1979 07  1742·
 1979 08  324.
 1979 09  819·
 1979 10  2510.
 1979 11  5814.
 1979 12  1713.
 1980 01 5018·
 1980 02 9112.
 1980 03 3812·
 1980 04 5415·
 1980 05 9526·
 1980 06 5932·
 1980 07 6535.
 1980 08 5231·
 1980 09 1130·
 1980 10 2830.
 1980 11 6920·
 1980 12 7528·
 1981 01  9233·
 1981 02  2517·
 1981 03  722.
 1981 04  819·
 1981 05  5814.
 1981 06  9922.
 1981 07  6218·
 1981 08  6714.
 1981 09  5313.
 1981 10  2714·
 1981 11  3910·
 1981 12  889.
 1982 01 467·
 1982 02 818·
 1982 03 7119·
 1982 04 3525·
 1982 05 3123·
 1982 06 6729.
 1982 07 1332.
 1982 08 9526·
 1982 09 2710·
 1982 10 5618·
 1982 11 4811.
 1982 12 8216.
 1983 01  7818.
 1983 02  5023.
 1983 03  8322.
 1983 04  338.
 1983 05  5321·
 1983 06  4825.
 1983 07  4821.
 1983 08  1125.
 1983 09  4817.
 1983 10  7721·
 1983 11  128·
 1983 12  325.
 1984 01 7920·
 1984 02 8722·
 1984 03 2323·
 1984 04 2420·
 1984 05 9326·
 1984 06 5331·
 1984 07 2130.
 1984 08 1021·
 1984 09 5818.
 1984 10 7616·
 1984 11 2618·
 1984 12 2518·
 1985 01  6815.
 1985 02  8024·
 1985 03  9620.
 1985 04  5714·
 1985 05  429·
 1985 06  1712·
 1985 07  1115·
 1985 08  1814.
 1985 09  252.
 1985 10  624.
 1985 11  7811·
 1985 12  464·
 1986 01 857.
 1986 02 14
 1986 03 303·
 1986 04 58.
 1986 05 171·
 1986 06 17·
 1986 07 2221.
 1986 08 8126.
 1986 09 406.
 1986 10 719·
 1986 11 3610.
 1986 12 896.
 1987 01  983.
 1987 02  05.
 1987 03  806.
 1987 04  656.
 1987 05  60
 1987 06  909·
 1987 07  8413.
 1987 08  7421.
 1987 09  2012.
 1987 10  6410·
 1987 11  5
 1987 12  23·
 1988 01 9711.
 1988 02 745.
 1988 03 251·
 1988 04 627.
 1988 05 371.
 1988 06 9430·
 1988 07 513·
 1988 08 9324·
 1988 09 613.
 1988 10 267·
 1988 11 139·
 1988 12 576·
 1989 01  17.
 1989 02  9513·
 1989 03  70
 1989 04  4314·
 1989 05  4010.
 1989 06  507·
 1989 07  27.
 1989 08  6215·
 1989 09  667.
 1989 10  684·
 1989 11  163.
 1989 12  542.
 1990 01 512.
 1990 02 497.
 1990 03 438.
 1990 04 8011.
 1990 05 8610·
 1990 06 189.
 1990 07 4121·
 1990 08 2912·
 1990 09 9212·
 1990 10 267·
 1990 11 917·
 1990 12 145·
 1991 01  137.
 1991 02  474.
 1991 03  06·
 1991 04  734.
 1991 05  175·
 1991 06  835·
 1991 07  995.
 1991 08  689·
 1991 09  996.
 1991 10  594.
 1991 11  44
 1992 01 879.
 1992 02 793·
 1992 03 259·
 1992 04 1910.
 1992 05 4311.
 1992 06 09.
 1992 07 576.
 1992 08 2813.
 1992 09 755.
 1992 10 312·
 1992 11 547·
 1992 12 58·
 1993 01  4516·
 1993 02  6725·
 1993 03  439.
 1993 04  413.
 1993 05  409.
 1993 06  2611.
 1993 07  7423.
 1993 08  920.
 1993 09  7511·
 1993 10  53
 1993 11  2113·
 1993 12  264·
 1994 01 86
 1994 02 170·
 1994 03 865.
 1994 04 869·
 1994 05 362.
 1994 06 128·
 1994 07 9512.
 1994 08 4616·
 1994 09 156.
 1994 10 584.
 1994 11 966·
 1994 12 886.
 1995 01  335.
 1995 02  98
 1995 03  664·
 1995 04  184.
 1995 05  306.
 1995 06  17·
 1995 07  54.
 1995 08  687.
 1995 09  6812.
 1995 10  62
 1995 11  394.
 1995 12  953.
 1996 01 355.
 1996 02 9913.
 1996 03 174.
 1996 04 7917·
 1996 05 4314·
 1996 06 5816.
 1996 07 166.
 1996 08 29
 1996 09 323.
 1996 10 74·
 1996 11 355.
 1996 12 754·
 1997 01  631·
 1997 02  409.
 1997 03  110·
 1997 04  759·
 1997 05  25
 1997 06  7610·
 1997 07  6219·
 1997 08  918.
 1997 09  311·
 1997 10  607.
 1997 11  96
 1997 12  85
 1998 01 181·
 1998 02 605.
 1998 03 210.
 1998 04 3310.
 1998 05 49
 1998 06 717·
 1998 07 514·
 1998 08 124.
 1998 09 122.
 1998 10 124·
 1998 11 564.
 1999 01  29.
 1999 02  204·
 1999 03  285.
 1999 04  313.
 1999 05  90.
 1999 06  124.
 1999 07  8612·
 1999 08  308.
 1999 09  679.
 1999 10  497.
 1999 11  825.
 1999 12  774.
 2000 01 304·
 2000 02 195.
 2000 04 34
 2000 06 2410·
 2000 07 826·
 2000 08 3713.
 2000 09 8611·
 2000 10 4710.
 2000 11 2812·
 2000 12 397·
 2001 01  911·
 2001 02  449·
 2001 03  113.
 2001 04  88
 2001 06  9517·
 2001 07  42
 2001 08  565·
 2001 09  733·
 2001 10  651·
 2001 11  913.
 2001 12  763·
 2002 02 51·
 2002 03 613.
 2002 04 675·
 2002 05 662.
 2002 06 241.
 2002 07 546·
 2002 08 704·
 2002 09 60
 2002 10 926.
 2002 11 389.
 2002 12 256·
 2003 01  134·
 2003 02  976·
 2003 03  314·
 2003 04  824·
 2003 05  74.
 2003 06  514.
 2003 07  784·
 2003 08  188.
 2003 09  497.
 2003 10  934·
 2003 11  47
 2003 12  327.
 2004 01 706·
 2004 02 869.
 2004 03 3410·
 2004 04 504.
 2004 05 279.
 2004 06 1713.
 2004 07 576.
 2004 10 222·
 2004 12 1
 2005 01  996·
 2005 02  60
 2005 03  246.
 2005 04  08·
 2005 05  70
 2005 06  125·
 2005 08  561·
 2005 10  553·
 2005 11  94
 2005 12  93·
 2006 01 433·
 2006 02 226.
 2006 04 571·
 2006 06 679·
 2006 07 3611.
 2006 08 84
 2006 09 733·
 2006 11 333·
 2006 12 102.
 2007 01  4611.
 2007 02  816·
 2007 03  756.
 2007 04  669.
 2007 05  410·
 2007 06  4115·
 2007 07  8717.
 2007 08  288·
 2007 09  25
 2007 10  442.
 2007 11  882.
 2007 12  481·
 2008 01 793·
 2008 02 05·
 2008 03 235.
 2008 04 114·
 2008 05 1112.
 2008 06 493.
 2008 07 603·
 2008 08 875·
 2008 09 523.
 2008 10 533.
 2008 11 94
 2008 12 326.
 2009 02  594.
 2009 05  19.
 2009 06  4311.
 2009 07  85
 2009 08  13
 2009 09  44·
 2009 10  532.
 2009 11  233·
 2009 12  214.
 2010 01 10.
 2010 02 920.
 2010 03 45
 2010 04 148.
 2010 05 554.
 2010 06 5413·
 2010 07 7812.
 2010 08 504.
 2010 09 541.
 2010 10 596.
 2010 11 715·
 2010 12 94·
 2011 01  10
 2011 02  504·
 2011 03  994.
 2011 04  997.
 2011 05  623·
 2011 06  975·
 2011 07  646.
 2011 08  518·
 2011 09  72
 2011 10  931·
 2011 11  910.
 2011 12  223·
 2012 01 282·
 2012 02 595.
 2012 03 304·
 2012 04 9417·
 2012 05 439.
 2012 06 388·
 2012 07 5612·
 2012 08 727·
 2012 09 5511·
 2012 10 990.
 2012 11 703.
 2012 12 893·
 2013 01  27
 2013 02  360·
 2013 03  984.
 2013 04  21.
 2013 05  471·
 2013 06  694.
 2013 07  884.
 2013 08  917.
 2013 09  284·
 2013 10  425·
 2013 11  1820.
 2013 12  6414·
 2014 01 720·
 2014 02 2319·
 2014 03 8712.
 2014 04 524·
 2014 05 486.
 2014 06 72·
 2014 07 2110.
 2014 08 138.
 2014 09 384·
 2014 10 140.
 2014 11 715.
 2014 12 260.
 2015 01  900.
 2015 02  870·
 2015 03  100.
 2015 04  03·
 2015 05  420·
 2015 06  951.
 2015 07  4110·
 2015 08  665·
 2015 09  581.
 2015 10  32
 2015 11  884·
 2015 12  800.
 2016 01 240·
 2016 02 191·
 2016 03 21.
 2016 04 252·
 2016 05 54
 2016 06 983.
 2016 07 5811.
 2016 08 63·
 2016 09 860.
 2016 10 39


 2016 11 564.
 2016 12 559.
 2017 01  828·
 2017 02  365.
 2017 03  227.
 2017 04  3010·
 2017 05  310·
 2017 06  80.
 2017 07  71.
 2017 08  117.
 2017 09  451.
 2017 10  04·
 2017 11  851.
 2017 12  68.
 2018 01 63
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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: Nonagriculture, Unpaid Family Workers, 16-19 years, 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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