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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 7130·
 1976 07 3629.
 1976 08 7233.
 1976 09 217.
 1976 10 6918·
 1976 11 238.
 1976 12 1214·
 1977 01  1710.
 1977 02  9717·
 1977 03  7124.
 1977 04  1530.
 1977 05  9325·
 1977 06  431·
 1977 07  6234.
 1977 08  9525·
 1977 09  7511·
 1977 10  6616.
 1977 11  213.
 1977 12  8915.
 1978 01 3120·
 1978 02 8222.
 1978 03 2226·
 1978 04 5918.
 1978 05 5624·
 1978 06 7926·
 1978 07 8130·
 1978 08 9532·
 1978 09 6810.
 1978 10 710·
 1978 11 5810·
 1978 12 914·
 1979 01  1217.
 1979 02  4120·
 1979 03  6116·
 1979 04  3824·
 1979 05  5725·
 1979 06  8125·
 1979 07  2242.
 1979 08  4624·
 1979 09  9819.
 1979 10  5410·
 1979 11  9714·
 1979 12  2113·
 1980 01 5318·
 1980 02 912.
 1980 03 6812.
 1980 04 7515·
 1980 05 6626.
 1980 06 2132.
 1980 07 4135·
 1980 08 4631.
 1980 09 630·
 1980 10 9230.
 1980 11 4820.
 1980 12 9728·
 1981 01  6933·
 1981 02  4617·
 1981 03  4522.
 1981 04  1719·
 1981 05  7214·
 1981 06  3422.
 1981 07  1518·
 1981 08  1714.
 1981 09  6013·
 1981 10  3214·
 1981 11  6410·
 1981 12  37
 1982 01 37·
 1982 02 3918·
 1982 03 2319·
 1982 04 3825·
 1982 05 9323.
 1982 06 8129·
 1982 07 5032.
 1982 08 926·
 1982 09 5110.
 1982 10 918·
 1982 11 2611.
 1982 12 6216.
 1983 01  2118.
 1983 02  9723.
 1983 03  5722·
 1983 04  368.
 1983 05  7121.
 1983 06  4725.
 1983 07  7521.
 1983 08  9325.
 1983 09  9717·
 1983 10  8421.
 1983 11  3728·
 1983 12  2225·
 1984 01 1620·
 1984 02 5722·
 1984 03 2423.
 1984 04 3420·
 1984 05 7326·
 1984 06 4331·
 1984 07 4430.
 1984 08 6921·
 1984 09 3718.
 1984 10 4216·
 1984 11 2718.
 1984 12 8818·
 1985 01  315.
 1985 02  7924·
 1985 03  3020.
 1985 04  8114·
 1985 05  909.
 1985 06  512·
 1985 07  3615·
 1985 08  5814·
 1985 09  412.
 1985 10  944.
 1985 11  5011.
 1985 12  604·
 1986 01 26
 1986 02 48
 1986 03 43.
 1986 04 488.
 1986 05 391·
 1986 06 927·
 1986 07 5521.
 1986 08 1026.
 1986 09 996.
 1986 10 769.
 1986 11 8510·
 1986 12 606.
 1987 01  503·
 1987 02  765·
 1987 03  06.
 1987 04  346·
 1987 05  623.
 1987 06  919·
 1987 07  3213.
 1987 08  9721.
 1987 09  2812.
 1987 10  4810.
 1987 11  375.
 1987 12  353.
 1988 01 6811·
 1988 02 965·
 1988 03 971.
 1988 04 637.
 1988 05 251.
 1988 06 1230·
 1988 07 203.
 1988 08 1724.
 1988 09 7013·
 1988 10 957.
 1988 11 359·
 1988 12 606·
 1989 01  957.
 1989 02  7113.
 1989 03  15.
 1989 04  8114.
 1989 05  2110·
 1989 06  90
 1989 07  987·
 1989 08  9315·
 1989 09  927·
 1989 10  294.
 1989 11  33
 1989 12  332.
 1990 01 752·
 1990 02 867.
 1990 03 398·
 1990 04 6311.
 1990 05 6710·
 1990 06 879.
 1990 07 7121.
 1990 08 7312·
 1990 09 8512·
 1990 10 847·
 1990 11 117·
 1990 12 755.
 1991 01  747·
 1991 02  504.
 1991 03  67
 1991 04  74.
 1991 05  35·
 1991 06  885.
 1991 07  685·
 1991 08  319.
 1991 09  676.
 1991 10  214·
 1991 11  73
 1992 01 369.
 1992 02 833.
 1992 03 19.
 1992 04 6310.
 1992 05 3411.
 1992 06 989·
 1992 07 26·
 1992 08 4413.
 1992 09 645.
 1992 10 782·
 1992 11 267·
 1992 12 488.
 1993 01  8816.
 1993 02  2025.
 1993 03  979·
 1993 04  3213.
 1993 05  959·
 1993 06  4211·
 1993 07  6723·
 1993 08  7720.
 1993 09  9611·
 1993 10  875·
 1993 11  913.
 1993 12  904.
 1994 01 302.
 1994 02 260·
 1994 03 265.
 1994 04 39·
 1994 05 602·
 1994 06 528.
 1994 07 4112.
 1994 08 7216·
 1994 09 746.
 1994 10 854.
 1994 11 76.
 1994 12 806·
 1995 01  845·
 1995 02  684.
 1995 03  974.
 1995 04  314·
 1995 05  296.
 1995 06  71
 1995 07  124·
 1995 08  59
 1995 09  7112.
 1995 10  885·
 1995 11  784.
 1995 12  203.
 1996 01 995·
 1996 02 3813·
 1996 03 454·
 1996 04 9517.
 1996 05 2514·
 1996 06 6516.
 1996 07 896.
 1996 08 914.
 1996 09 863·
 1996 10 384·
 1996 11 105.
 1996 12 404.
 1997 01  47
 1997 02  529·
 1997 03  3310.
 1997 04  99
 1997 05  959·
 1997 06  2610.
 1997 07  819.
 1997 08  4818.
 1997 09  421.
 1997 10  37.
 1997 11  125·
 1997 12  952.
 1998 01 271.
 1998 02 535·
 1998 03 4410.
 1998 04 7210.
 1998 05 136·
 1998 06 707.
 1998 07 3014·
 1998 08 344·
 1998 09 862.
 1998 10 734·
 1998 11 204·
 1999 01  659.
 1999 02  624·
 1999 03  7
 1999 04  903·
 1999 05  690·
 1999 06  764.
 1999 07  4012.
 1999 08  398.
 1999 09  799.
 1999 10  937.
 1999 11  675.
 1999 12  944.
 2000 01 52
 2000 02 995·
 2000 04 65.
 2000 06 510·
 2000 07 696.
 2000 08 813·
 2000 09 211.
 2000 10 4810·
 2000 11 3712.
 2000 12 58
 2001 01  2411·
 2001 02  219.
 2001 03  8713·
 2001 04  126·
 2001 06  6717.
 2001 07  529.
 2001 08  765.
 2001 09  573.
 2001 10  48
 2001 11  903·
 2001 12  863·
 2002 02 71.
 2002 03 133·
 2002 04 115·
 2002 05 242·
 2002 06 991·
 2002 07 316.
 2002 08 154·
 2002 09 202.
 2002 10 966.
 2002 11 959.
 2002 12 276·
 2003 01  324.
 2003 02  866·
 2003 03  264.
 2003 04  98
 2003 05  424.
 2003 06  834.
 2003 07  664.
 2003 08  48.
 2003 09  557.
 2003 10  234.
 2003 11  854·
 2003 12  447·
 2004 01 4
 2004 02 709.
 2004 03 7810·
 2004 04 454.
 2004 05 45
 2004 06 1113.
 2004 07 636·
 2004 10 562·
 2004 12 602·
 2005 01  606.
 2005 02  846.
 2005 03  536.
 2005 04  558.
 2005 05  552·
 2005 06  125·
 2005 08  361.
 2005 10  63
 2005 11  585·
 2005 12  393.
 2006 01 303.
 2006 02 396.
 2006 04 571.
 2006 06 859·
 2006 07 8711.
 2006 08 665·
 2006 09 653·
 2006 11 943·
 2006 12 812.
 2007 01  5011.
 2007 02  206.
 2007 03  366·
 2007 04  13
 2007 05  230.
 2007 06  8615.
 2007 07  317.
 2007 08  8
 2007 09  410.
 2007 10  482.
 2007 11  172.
 2007 12  171·
 2008 01 853.
 2008 02 225.
 2008 03 205.
 2008 04 1514.
 2008 05 6412·
 2008 06 443.
 2008 07 823·
 2008 08 25·
 2008 09 83·
 2008 10 78
 2008 11 973·
 2008 12 46.
 2009 02  73
 2009 05  11
 2009 06  8411.
 2009 07  716·
 2009 08  43
 2009 09  564·
 2009 10  872.
 2009 11  793.
 2009 12  224.
 2010 01 510.
 2010 02 750·
 2010 03 280.
 2010 04 438.
 2010 05 604.
 2010 06 4313.
 2010 07 4312·
 2010 08 634·
 2010 09 691·
 2010 10 106·
 2010 11 755·
 2010 12 634.
 2011 01  927·
 2011 02  204.
 2011 03  984.
 2011 04  507.
 2011 05  673.
 2011 06  415.
 2011 07  156·
 2011 08  558.
 2011 09  561·
 2011 10  69
 2011 11  490.
 2011 12  353.
 2012 01 482·
 2012 02 225·
 2012 03 52
 2012 04 7117.
 2012 05 559.
 2012 06 448.
 2012 07 9812·
 2012 08 717.
 2012 09 1511.
 2012 10 5
 2012 11 883.
 2012 12 663.
 2013 01  923.
 2013 02  980.
 2013 03  484.
 2013 04  131.
 2013 05  721·
 2013 06  434.
 2013 07  284.
 2013 08  927.
 2013 09  704·
 2013 10  845.
 2013 11  220·
 2013 12  1214·
 2014 01 2220.
 2014 02 9019·
 2014 03 7312·
 2014 04 34·
 2014 05 926·
 2014 06 562·
 2014 07 6410·
 2014 08 23
 2014 09 684.
 2014 10 990·
 2014 11 27
 2014 12 520.
 2015 01  620·
 2015 02  660.
 2015 03  370.
 2015 04  973.
 2015 05  130·
 2015 06  231·
 2015 07  9410·
 2015 08  915·
 2015 09  821·
 2015 10  672·
 2015 11  244.
 2015 12  890.
 2016 01 590·
 2016 02 151.
 2016 03 761·
 2016 04 742.
 2016 05 565·
 2016 06 133·
 2016 07 2711·
 2016 08 52


 2016 09 110·
 2016 10 295.
 2016 11 774·
 2016 12 549.
 2017 01  878.
 2017 02  575.
 2017 03  517.
 2017 04  3810.
 2017 05  710·
 2017 06  160.
 2017 07  991·
 2017 08  847·
 2017 09  771·
 2017 10  524.
 2017 11  971.
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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

Unemployment data for every county in the U.S..
Click for Illinois counties, then follow the example for your state

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