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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 07 814.
 1976 08 843·
 1976 09 982·
 1976 10 682.
 1976 11 662.
 1976 12 647.
 1977 01  362.
 1977 02  882.
 1977 03  55.
 1977 04  293·
 1977 05  634.
 1977 06  951.
 1977 07  480.
 1977 08  631.
 1977 09  920.
 1977 11  311.
 1977 12  711.
 1978 01 701.
 1978 02 592.
 1978 03 682.
 1978 06 742.
 1978 07 830.
 1978 08 290·
 1978 09 973·
 1978 10 822.
 1978 12 592.
 1979 01  881.
 1979 03  407·
 1979 04  466.
 1979 05  793·
 1979 06  51
 1979 07  395.
 1979 08  420.
 1979 09  500.
 1979 10  543.
 1980 03 641.
 1980 04 686·
 1980 05 45·
 1980 06 614·
 1980 07 103·
 1980 08 522.
 1980 09 962·
 1980 10 592·
 1980 11 953·
 1980 12 433.
 1981 01  92·
 1981 02  621.
 1981 03  633.
 1981 04  174·
 1981 05  501·
 1981 06  75.
 1981 07  841·
 1981 08  743.
 1981 09  494.
 1981 10  57
 1981 11  512.
 1981 12  402.
 1982 01 642·
 1982 02 19.
 1982 03 855·
 1982 04 642.
 1982 05 771.
 1982 06 503.
 1982 10 282.
 1982 12 231.
 1983 06  93
 1984 01 434.
 1984 02 503·
 1984 03 172·
 1984 04 452·
 1984 05 431.
 1984 06 461.
 1984 09 702.
 1984 12 90
 1985 01  382·
 1985 03  346·
 1985 04  344.
 1985 05  82.
 1985 07  404·
 1985 08  594.
 1985 10  84
 1985 11  63.
 1986 01 881·
 1986 03 891.
 1986 06 20
 1986 07 171.
 1986 08 441.
 1986 09 20
 1986 10 684·
 1986 11 972·
 1986 12 961.
 1987 01  693.
 1987 02  781·
 1987 04  274·
 1987 05  585·
 1987 06  813.
 1987 07  251.
 1987 08  14
 1987 09  661.
 1987 10  264·
 1987 11  106·
 1987 12  895.
 1988 01 842·
 1988 02 972.
 1988 04 592.
 1988 05 106.
 1988 06 010·
 1988 07 132·
 1988 08 212.
 1988 09 581.
 1988 10 272.
 1988 11 192·
 1988 12 723.
 1989 01  404.
 1989 02  22.
 1989 03  84
 1989 04  1210·
 1989 05  878·
 1989 06  8910·
 1989 07  22.
 1989 08  671.
 1989 09  567.
 1989 10  751·
 1990 02 92
 1990 03 872·
 1990 04 283.
 1990 05 732.
 1990 06 991·
 1990 09 482.
 1990 10 112.
 1990 12 222·
 1991 02  905.
 1991 03  502·
 1991 04  353·
 1991 06  832.
 1991 07  625.
 1991 08  183·
 1991 11  582.
 1991 12  462.
 1992 01 32
 1992 02 33.
 1992 03 613.
 1992 04 223·
 1992 05 441·
 1992 09 802.
 1992 10 51
 1992 11 507·
 1992 12 691.
 1993 01  492·
 1993 02  593·
 1993 03  922.
 1993 04  03.
 1993 05  375·
 1993 06  422.
 1993 07  371.
 1993 08  565.
 1993 09  929.
 1994 01 822·
 1994 02 970·
 1994 08 811.
 1994 09 921.
 1994 10 851.
 1994 11 110.
 1994 12 452·
 1995 01  351.
 1995 02  831.
 1995 03  416.
 1995 04  416·
 1995 05  486·
 1995 06  328·
 1995 07  745·
 1995 08  897.
 1995 09  814.
 1995 10  153.
 1995 11  252·
 1995 12  344·
 1996 01 92·
 1996 02 382.
 1996 03 30
 1996 04 433·
 1996 05 332.
 1996 06 322.
 1996 07 541.
 1996 08 113·
 1996 11 775.
 1996 12 550.
 1997 01  825.
 1997 04  582.
 1997 05  933·
 1997 06  873·
 1997 07  30
 1997 08  274·
 1997 09  565.
 1997 10  362.
 1998 03 334.
 1998 04 887·
 1998 08 66
 1998 09 320·
 1998 10 56
 1998 11 352·
 1999 02  490.
 1999 03  340·
 1999 04  860·
 1999 05  870·
 1999 06  552.
 1999 07  224.
 1999 08  366.
 1999 09  876·
 1999 10  59
 1999 11  32·
 1999 12  441·
 2000 05 60·
 2000 06 614.
 2000 07 83·
 2000 08 733.
 2000 09 386.
 2000 10 883·
 2000 11 950·
 2000 12 110·
 2001 01  00.
 2001 05  904·
 2001 06  444·
 2001 07  702.
 2001 08  392·
 2001 09  412.
 2001 10  642.
 2002 08 893·
 2003 01  222.
 2003 02  43
 2003 07  842.
 2003 11  303·
 2003 12  444·
 2004 01 204·
 2004 02 621.
 2004 03 814·
 2004 05 242.
 2004 06 242.
 2004 07 80
 2004 08 563.
 2004 09 61.
 2005 06  293·
 2005 07  443.
 2005 08  910.
 2005 09  591.
 2005 10  360.
 2006 06 862·
 2006 10 511.
 2008 01 780.
 2008 02 700·
 2008 03 621.
 2009 06  220.
 2009 07  820.
 2009 08  82
 2009 09  540.
 2009 10  190·
 2009 11  140.
 2009 12  472.
 2010 01 690.
 2010 02 770.
 2010 03 44
 2010 04 650.
 2010 05 380.
 2010 06 620·
 2010 07 660·
 2010 08 620.
 2010 09 183·
 2010 10 590.
 2010 11 00·
 2010 12 890.
 2011 01  900.
 2011 02  831·
 2011 03  881·
 2011 04  201.
 2011 05  621.
 2011 06  720·
 2011 07  21.
 2011 08  563.
 2011 09  653.
 2011 10  873·
 2011 11  330.
 2011 12  231·
 2012 01 56
 2012 02 170.
 2012 03 31.
 2012 04 701.
 2012 05 155·
 2012 06 755.
 2012 07 540·
 2012 08 730.
 2012 09 500·
 2012 10 990·
 2012 11 560.
 2012 12 331.
 2013 01  930.
 2013 02  520·
 2013 03  40.
 2013 04  750.
 2013 05  01·
 2013 06  21
 2013 07  150.
 2013 08  500.
 2013 09  530.
 2013 10  190·
 2013 11  36
 2013 12  323.
 2014 01 582·
 2014 02 853.
 2014 03 330·
 2014 04 220·
 2014 05 470·
 2014 06 810·
 2014 07 32·
 2014 08 460·
 2014 09 762.
 2014 10 950.
 2014 11 630·
 2014 12 531.
 2015 01  281.
 2015 02  400.
 2015 03  580.
 2015 04  201.
 2015 05  9
 2015 06  541.
 2015 07  58
 2015 08  471·
 2015 09  514·
 2015 10  00.
 2015 11  550.
 2015 12  59
 2016 01 90·
 2016 02 650·
 2016 03 710·
 2016 04 60.
 2016 05 672.
 2016 06 632.


 2016 07 470·
 2016 08 640·
 2016 09 30
 2016 10 320.
 2016 11 55
 2016 12 340.
 2017 01  300·
 2017 02  330.
 2017 03  870·
 2017 04  400·
 2017 05  240.
 2017 06  560·
 2017 07  630.
 2017 08  330·
 2017 09  94
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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
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