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 Series Title: Employment Level: Agriculture and Related Industries, Unpaid Family Workers, 35-44 years, Men: NSA
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 1976 07 434.
 1976 08 99
 1976 09 62·
 1976 10 292.
 1976 11 572·
 1976 12 817.
 1977 01  952·
 1977 02  232·
 1977 03  685·
 1977 04  923·
 1977 05  164.
 1977 06  471.
 1977 07  270·
 1977 08  15
 1977 09  820.
 1977 11  451.
 1977 12  101.
 1978 01 551·
 1978 02 312.
 1978 03 862.
 1978 06 16
 1978 07 450·
 1978 08 260·
 1978 09 643·
 1978 10 71
 1978 12 422.
 1979 01  551.
 1979 03  997.
 1979 04  26
 1979 05  263.
 1979 06  304·
 1979 07  355.
 1979 08  560.
 1979 09  50.
 1979 10  903·
 1980 03 40
 1980 04 616·
 1980 05 115.
 1980 06 974·
 1980 07 93.
 1980 08 672·
 1980 09 992·
 1980 10 392·
 1980 11 623·
 1980 12 243.
 1981 01  512·
 1981 02  301.
 1981 03  413.
 1981 04  84.
 1981 05  751·
 1981 06  75·
 1981 07  171.
 1981 08  183·
 1981 09  14.
 1981 10  321·
 1981 11  832.
 1981 12  812.
 1982 01 872.
 1982 02 959.
 1982 03 595·
 1982 04 47
 1982 05 14
 1982 06 73.
 1982 10 882.
 1982 12 901.
 1983 06  881·
 1984 01 74·
 1984 02 413·
 1984 03 122·
 1984 04 422·
 1984 05 571.
 1984 06 101.
 1984 09 382.
 1984 12 322.
 1985 01  462.
 1985 03  166.
 1985 04  184·
 1985 05  402·
 1985 07  864.
 1985 08  24.
 1985 10  272·
 1985 11  713.
 1986 01 151.
 1986 03 371.
 1986 06 671·
 1986 07 591.
 1986 08 961.
 1986 09 164·
 1986 10 624.
 1986 11 592.
 1986 12 181.
 1987 01  583.
 1987 02  631.
 1987 04  534·
 1987 05  925·
 1987 06  63.
 1987 07  451.
 1987 08  481.
 1987 09  571.
 1987 10  314·
 1987 11  8
 1987 12  76
 1988 01 752.
 1988 02 262·
 1988 04 792.
 1988 05 936·
 1988 06 3510·
 1988 07 102.
 1988 08 7
 1988 09 801·
 1988 10 502.
 1988 11 272·
 1988 12 67
 1989 01  454.
 1989 02  572·
 1989 03  479.
 1989 04  6110.
 1989 05  198.
 1989 06  1910.
 1989 07  642·
 1989 08  131.
 1989 09  587·
 1989 10  241.
 1990 02 962·
 1990 03 742.
 1990 04 453.
 1990 05 852.
 1990 06 891.
 1990 09 202·
 1990 10 85
 1990 12 402·
 1991 02  115·
 1991 03  50
 1991 04  123·
 1991 06  52
 1991 07  565.
 1991 08  90
 1991 11  802.
 1991 12  82·
 1992 01 433.
 1992 02 913·
 1992 03 723.
 1992 04 223·
 1992 05 171.
 1992 09 282.
 1992 10 95
 1992 11 31
 1992 12 461·
 1993 01  1
 1993 02  803·
 1993 03  99
 1993 04  263·
 1993 05  355.
 1993 06  842·
 1993 07  131·
 1993 08  745.
 1993 09  829·
 1994 01 882·
 1994 02 860.
 1994 08 361·
 1994 09 161·
 1994 10 991·
 1994 11 560.
 1994 12 802·
 1995 01  381.
 1995 02  491.
 1995 03  866.
 1995 04  06·
 1995 05  736·
 1995 06  948·
 1995 07  645.
 1995 08  167·
 1995 09  71
 1995 10  173·
 1995 11  22·
 1995 12  714.
 1996 01 92.
 1996 02 232.
 1996 03 392·
 1996 04 353·
 1996 05 862·
 1996 06 442·
 1996 07 381.
 1996 08 23.
 1996 11 285.
 1996 12 370.
 1997 01  865.
 1997 04  922·
 1997 05  853.
 1997 06  833·
 1997 07  963·
 1997 08  474.
 1997 09  325.
 1997 10  90
 1998 03 64.
 1998 04 38
 1998 08 71
 1998 09 890.
 1998 10 791·
 1998 11 59
 1999 02  260.
 1999 03  360.
 1999 04  30·
 1999 05  280.
 1999 06  472·
 1999 07  134.
 1999 08  916·
 1999 09  906.
 1999 10  116·
 1999 11  272.
 1999 12  811.
 2000 05 140.
 2000 06 174.
 2000 07 93.
 2000 08 353·
 2000 09 946.
 2000 10 913.
 2000 11 17
 2000 12 410.
 2001 01  490.
 2001 05  844.
 2001 06  314.
 2001 07  132·
 2001 08  232.
 2001 09  702·
 2001 10  582.
 2002 08 893·
 2003 01  86
 2003 02  502.
 2003 07  302.
 2003 11  303·
 2003 12  324·
 2004 01 504.
 2004 02 41.
 2004 03 25
 2004 05 79
 2004 06 192·
 2004 07 615·
 2004 08 883·
 2004 09 731.
 2005 06  343.
 2005 07  83·
 2005 08  55
 2005 09  811.
 2005 10  940.
 2006 06 77
 2006 10 90
 2008 01 990.
 2008 02 260·
 2008 03 231.
 2009 06  800·
 2009 07  450.
 2009 08  780.
 2009 09  300.
 2009 10  390.
 2009 11  640.
 2009 12  28
 2010 01 30.
 2010 02 50.
 2010 03 243·
 2010 04 750.
 2010 05 740·
 2010 06 390·
 2010 07 200.
 2010 08 440·
 2010 09 993.
 2010 10 310.
 2010 11 71
 2010 12 870·
 2011 01  610·
 2011 02  931·
 2011 03  201·
 2011 04  771.
 2011 05  661·
 2011 06  630·
 2011 07  38
 2011 08  173·
 2011 09  463·
 2011 10  33·
 2011 11  190.
 2011 12  301.
 2012 01 570.
 2012 02 20.
 2012 03 811·
 2012 04 691·
 2012 05 815·
 2012 06 735.
 2012 07 68
 2012 08 70.
 2012 09 240·
 2012 10 540·
 2012 11 510·
 2012 12 451.
 2013 01  190·
 2013 02  70·
 2013 03  22
 2013 04  9
 2013 05  221.
 2013 06  200·
 2013 07  10.
 2013 08  500·
 2013 09  130·
 2013 10  6
 2013 11  321·
 2013 12  413·
 2014 01 22.
 2014 02 33·
 2014 03 850.
 2014 04 85
 2014 05 170·
 2014 06 750·
 2014 07 532·
 2014 08 60·
 2014 09 18
 2014 10 80.
 2014 11 560.
 2014 12 551·
 2015 01  841·
 2015 02  160·
 2015 03  380.
 2015 04  61.
 2015 05  231.
 2015 06  361·
 2015 07  671.
 2015 08  611.
 2015 09  664·
 2015 10  320·
 2015 11  380·
 2015 12  450.
 2016 01 710.
 2016 02 920.
 2016 03 710.
 2016 04 80·
 2016 05 182.
 2016 06 272.
 2016 07 90·
 2016 08 26


 2016 09 140·
 2016 10 770·
 2016 11 210·
 2016 12 990.
 2017 01  910·
 2017 02  4
 2017 03  2
 2017 04  520.
 2017 05  50·
 2017 06  960.
 2017 07  71
 2017 08  360.
 2017 09  391·
 2017 10  661·
 2017 11  710.
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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, 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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