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 Series Title: Employment Level: Agriculture and Related Industries, Unpaid Family Workers, 35-44 years: 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 7456.
 1976 07 9954·
 1976 08 8259·
 1976 09 1463·
 1976 10 971·
 1976 11 8462.
 1976 12 5653·
 1977 01  7438.
 1977 02  6838·
 1977 03  2333·
 1977 04  8755·
 1977 05  8975.
 1977 06  9979.
 1977 07  083.
 1977 08  8864.
 1977 09  348·
 1977 10  7954·
 1977 11  1963·
 1977 12  9638.
 1978 01 8530.
 1978 02 832·
 1978 03 1240.
 1978 04 7640·
 1978 05 3052.
 1978 06 1057·
 1978 07 3777·
 1978 08 1452.
 1978 09 5646.
 1978 10 3857.
 1978 11 7544·
 1978 12 2441·
 1979 01  720·
 1979 02  6525.
 1979 03  3340·
 1979 04  4442.
 1979 05  5455.
 1979 06  9265.
 1979 07  4271·
 1979 08  3648.
 1979 09  8948·
 1979 10  4662.
 1979 11  5849.
 1979 12  8840·
 1980 01 3230.
 1980 02 7525·
 1980 03 6430·
 1980 04 1349·
 1980 05 2868·
 1980 06 5671·
 1980 07 6685·
 1980 08 5062·
 1980 09 4458.
 1980 10 8859.
 1980 11 9649.
 1980 12 6040.
 1981 01  7735·
 1981 02  9843.
 1981 03  1138.
 1981 04  3244·
 1981 05  4439·
 1981 06  3647·
 1981 07  9151.
 1981 08  7944.
 1981 09  8933·
 1981 10  7747.
 1981 11  4448.
 1981 12  3925·
 1982 01 8331.
 1982 02 2132·
 1982 03 125.
 1982 04 7435.
 1982 05 1843.
 1982 06 9458.
 1982 07 2055·
 1982 08 7257·
 1982 09 1544·
 1982 10 4646·
 1982 11 8142·
 1982 12 4727.
 1983 01  1720.
 1983 02  5321.
 1983 03  9137.
 1983 04  3625·
 1983 05  9335.
 1983 06  1550.
 1983 07  8245.
 1983 08  241·
 1983 09  3836.
 1983 10  5740.
 1983 11  1134.
 1983 12  3331.
 1984 01 7126·
 1984 02 3020·
 1984 03 5930.
 1984 04 4234.
 1984 05 3544·
 1984 06 1052.
 1984 07 3258·
 1984 08 6757.
 1984 09 143·
 1984 10 9533·
 1984 11 6331.
 1984 12 7036·
 1985 01  6236.
 1985 02  1329.
 1985 03  855.
 1985 04  4033.
 1985 05  3749.
 1985 06  1341.
 1985 07  4944·
 1985 08  8932·
 1985 09  7024·
 1985 10  7123·
 1985 11  9322.
 1985 12  5618·
 1986 01 3121·
 1986 02 8714.
 1986 03 7033.
 1986 04 321.
 1986 05 1430·
 1986 06 8742·
 1986 07 3838·
 1986 08 1827·
 1986 09 3716.
 1986 10 2026.
 1986 11 7831.
 1986 12 1418·
 1987 01  4626.
 1987 02  6316.
 1987 03  9718.
 1987 04  2821.
 1987 05  924·
 1987 06  1519.
 1987 07  2716.
 1987 08  2521.
 1987 09  2014.
 1987 10  324.
 1987 11  2440·
 1987 12  9125·
 1988 01 9825·
 1988 02 7628·
 1988 03 7016.
 1988 04 4016.
 1988 05 8836.
 1988 06 1035·
 1988 07 7126.
 1988 08 925.
 1988 09 5913·
 1988 10 525.
 1988 11 6022.
 1988 12 6121.
 1989 01  415·
 1989 02  8719.
 1989 03  9234·
 1989 04  8526·
 1989 05  4335·
 1989 06  641·
 1989 07  5030.
 1989 08  9326·
 1989 09  2126·
 1989 10  3720·
 1989 11  3922·
 1989 12  2322·
 1990 01 68·
 1990 02 819.
 1990 03 9315.
 1990 04 3819·
 1990 05 9229·
 1990 06 6327·
 1990 07 6620.
 1990 08 2520·
 1990 09 9927·
 1990 10 3422·
 1990 11 4216.
 1990 12 9811·
 1991 01  7019.
 1991 02  6922.
 1991 03  2720·
 1991 04  9512·
 1991 05  7629·
 1991 06  6921·
 1991 07  5128.
 1991 08  7816.
 1991 09  917.
 1991 10  5813·
 1991 11  7312.
 1991 12  3610.
 1992 01 8912.
 1992 02 8716·
 1992 03 7311.
 1992 04 8118.
 1992 05 6113.
 1992 06 3236·
 1992 07 5825·
 1992 08 5126·
 1992 09 9316.
 1992 10 9322.
 1992 11 6024.
 1992 12 95.
 1993 01  7913·
 1993 02  9520·
 1993 03  3624.
 1993 04  4219.
 1993 05  3926·
 1993 06  8835.
 1993 07  6724·
 1993 08  6522.
 1993 09  1733.
 1993 10  4917.
 1993 11  5914·
 1993 12  1416.
 1994 01 824·
 1994 02 782·
 1994 03 454.
 1994 04 537.
 1994 05 287·
 1994 06 998.
 1994 07 8110.
 1994 08 706·
 1994 09 744.
 1994 10 641.
 1994 11 482·
 1994 12 775.
 1995 01  653.
 1995 02  473·
 1995 03  549.
 1995 04  1214·
 1995 05  6913.
 1995 06  5014·
 1995 07  3015.
 1995 08  3812·
 1995 09  806·
 1995 10  975.
 1995 11  323·
 1995 12  435·
 1996 01 195·
 1996 02 383.
 1996 03 43
 1996 04 405.
 1996 05 287·
 1996 06 507.
 1996 07 696.
 1996 08 6710.
 1996 09 784.
 1996 10 334·
 1996 11 419.
 1996 12 874.
 1997 01  61
 1997 02  121·
 1997 03  162·
 1997 04  874·
 1997 05  998.
 1997 06  3710·
 1997 07  7613.
 1997 08  8111·
 1997 09  339·
 1997 10  83
 1997 11  276.
 1997 12  63.
 1998 01 344.
 1998 02 534.
 1998 03 2
 1998 04 257.
 1998 05 96
 1998 06 692·
 1998 07 56
 1998 08 277.
 1998 09 381·
 1998 10 842.
 1998 11 717·
 1998 12 23
 1999 02  41.
 1999 03  72
 1999 04  551.
 1999 05  531·
 1999 06  635.
 1999 07  3417.
 1999 08  3818.
 1999 09  7818·
 1999 10  1022.
 1999 11  957·
 1999 12  788.
 2000 01 874·
 2000 02 622·
 2000 03 52·
 2000 04 55
 2000 05 937.
 2000 06 664.
 2000 07 407·
 2000 08 776.
 2000 09 336.
 2000 10 893.
 2000 11 1
 2000 12 75
 2001 01  710·
 2001 02  260·
 2001 03  130.
 2001 04  6
 2001 05  936.
 2001 06  974.
 2001 07  255·
 2001 08  522·
 2001 09  143.
 2001 10  44
 2001 12  142.
 2002 02 180.
 2002 03 723.
 2002 04 38
 2002 05 803.
 2002 07 384·
 2002 08 283.
 2002 09 722·
 2002 10 485·
 2002 11 665.
 2002 12 715.
 2003 01  667.
 2003 02  694.
 2003 03  863·
 2003 04  131·
 2003 05  630·
 2003 06  180.
 2003 07  43.
 2003 08  94
 2003 09  342.
 2003 10  951·
 2003 11  513.
 2003 12  745.
 2004 01 715.
 2004 02 272.
 2004 03 835.
 2004 05 442·
 2004 06 95
 2004 07 627.
 2004 08 845·
 2004 09 142·
 2004 10 492·
 2005 01  772.
 2005 02  585.
 2005 03  24
 2005 04  22.
 2005 06  723.
 2005 07  396.
 2005 08  36
 2005 09  491.
 2005 10  73
 2005 11  821.
 2005 12  371.
 2006 01 93·
 2006 05 292·
 2006 06 69
 2006 07 424.
 2006 08 25
 2006 10 161.
 2007 01  72.
 2007 02  873.
 2007 03  683·
 2007 04  353.
 2007 05  281·
 2007 06  360.
 2007 07  307·
 2007 08  110·
 2007 09  884.
 2007 11  770.
 2007 12  320.
 2008 01 951·
 2008 02 682.
 2008 03 221·
 2008 04 182.
 2008 05 611.
 2008 12 764.
 2009 01  93·
 2009 06  560.
 2009 07  100·
 2009 08  421.
 2009 09  21·
 2009 10  402.
 2009 11  680·
 2009 12  253.
 2010 01 870.
 2010 02 910·
 2010 03 843·
 2010 04 40·
 2010 05 793·
 2010 06 510·
 2010 07 35
 2010 08 88
 2010 09 143.
 2010 10 912·
 2010 11 212.
 2010 12 72·
 2011 01  562·
 2011 02  41.
 2011 03  674·
 2011 04  19
 2011 05  931.
 2011 06  90.
 2011 07  231.
 2011 08  4
 2011 09  385.
 2011 10  51
 2011 11  652·
 2011 12  703·
 2012 01 280·
 2012 02 993·
 2012 03 934·
 2012 04 484·
 2012 05 268.
 2012 06 465·
 2012 07 330·
 2012 08 940.
 2012 09 200.
 2012 10 130.
 2012 11 360.
 2012 12 923.
 2013 01  242·
 2013 02  423·
 2013 03  753.
 2013 04  463·
 2013 05  74
 2013 06  40·
 2013 07  52
 2013 08  890.
 2013 09  353·
 2013 10  920·
 2013 11  93
 2013 12  773.
 2014 01 932.
 2014 02 264·
 2014 03 470·
 2014 04 920.
 2014 05 623.
 2014 06 490.
 2014 07 902.
 2014 08 410.
 2014 09 795.
 2014 10 310.
 2014 11 230.
 2014 12 55
 2015 01  81·
 2015 02  674.
 2015 03  708.
 2015 04  91
 2015 05  378·
 2015 06  745.
 2015 07  822.
 2015 08  311·
 2015 09  774·
 2015 10  970.
 2015 11  350.
 2015 12  804.
 2016 01 680.
 2016 02 61.
 2016 03 29
 2016 04 720·
 2016 05 712.
 2016 06 95
 2016 07 902·
 2016 08 620·
 2016 09 76


 2016 10 82
 2016 11 670.
 2016 12 320.
 2017 01  94
 2017 02  121.
 2017 03  364.
 2017 04  893·
 2017 05  64
 2017 06  534·
 2017 07  980.
 2017 08  641·
 2017 09  491.
 2017 10  11.
 2017 11  770.
 2017 12  15
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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: Agriculture and Related Industries, Unpaid Family Workers, 35-44 years: 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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