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 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  |  Yearly Chart  |  Excel file  |  Self-updating Excel file
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 1976 07 664.
 1976 08 133.
 1976 09 672·
 1976 10 612·
 1976 11 532·
 1976 12 47.
 1977 01  762·
 1977 02  602.
 1977 03  315·
 1977 04  183.
 1977 05  104.
 1977 06  841.
 1977 07  500.
 1977 08  371.
 1977 09  840.
 1977 11  751.
 1977 12  871·
 1978 01 671·
 1978 02 342.
 1978 03 32·
 1978 06 412·
 1978 07 410·
 1978 08 240·
 1978 09 623·
 1978 10 39
 1978 12 162·
 1979 01  411.
 1979 03  727.
 1979 04  296·
 1979 05  71
 1979 06  984·
 1979 07  765.
 1979 08  880.
 1979 09  160.
 1979 10  343·
 1980 03 431.
 1980 04 166·
 1980 05 805.
 1980 06 114.
 1980 07 68
 1980 08 39
 1980 09 202·
 1980 10 172.
 1980 11 703·
 1980 12 73.
 1981 01  192.
 1981 02  651·
 1981 03  923.
 1981 04  944·
 1981 05  831.
 1981 06  935.
 1981 07  51.
 1981 08  33.
 1981 09  434.
 1981 10  631.
 1981 11  22.
 1981 12  572·
 1982 01 572.
 1982 02 64
 1982 03 25.
 1982 04 82·
 1982 05 51·
 1982 06 93·
 1982 10 502.
 1982 12 311.
 1983 06  951.
 1984 01 344.
 1984 02 153·
 1984 03 252.
 1984 04 572·
 1984 05 51.
 1984 06 901.
 1984 09 182.
 1984 12 502.
 1985 01  72·
 1985 03  956·
 1985 04  584·
 1985 05  542.
 1985 07  544.
 1985 08  74
 1985 10  222.
 1985 11  763.
 1986 01 851·
 1986 03 971·
 1986 06 101·
 1986 07 47
 1986 08 611.
 1986 09 564·
 1986 10 464·
 1986 11 252·
 1986 12 711·
 1987 01  73
 1987 02  83
 1987 04  914·
 1987 05  275·
 1987 06  893.
 1987 07  941.
 1987 08  511·
 1987 09  681.
 1987 10  764·
 1987 11  806.
 1987 12  375.
 1988 01 562·
 1988 02 272.
 1988 04 672.
 1988 05 76·
 1988 06 8010·
 1988 07 602·
 1988 08 62.
 1988 09 401·
 1988 10 522.
 1988 11 212.
 1988 12 713·
 1989 01  454·
 1989 02  102·
 1989 03  789.
 1989 04  6210.
 1989 05  538·
 1989 06  1710·
 1989 07  252.
 1989 08  61.
 1989 09  207.
 1989 10  601·
 1990 02 822.
 1990 03 532·
 1990 04 283·
 1990 05 542.
 1990 06 931·
 1990 09 782.
 1990 10 842·
 1990 12 352.
 1991 02  275.
 1991 03  812·
 1991 04  193.
 1991 06  662·
 1991 07  785.
 1991 08  883.
 1991 11  90
 1991 12  36
 1992 01 643·
 1992 02 493·
 1992 03 793.
 1992 04 583·
 1992 05 321·
 1992 09 402·
 1992 10 92
 1992 11 687·
 1992 12 48
 1993 01  612·
 1993 02  613.
 1993 03  312·
 1993 04  8
 1993 05  375.
 1993 06  42
 1993 07  331.
 1993 08  315·
 1993 09  199·
 1994 01 172.
 1994 02 890.
 1994 08 611.
 1994 09 821.
 1994 10 941.
 1994 11 350·
 1994 12 67
 1995 01  271.
 1995 02  31·
 1995 03  35
 1995 04  43
 1995 05  796.
 1995 06  18·
 1995 07  765·
 1995 08  87.
 1995 09  884·
 1995 10  693·
 1995 11  722.
 1995 12  74·
 1996 01 302·
 1996 02 152.
 1996 03 60
 1996 04 83·
 1996 05 52·
 1996 06 702.
 1996 07 31.
 1996 08 63·
 1996 11 385·
 1996 12 910.
 1997 01  895.
 1997 04  202.
 1997 05  813·
 1997 06  593·
 1997 07  323.
 1997 08  944.
 1997 09  75.
 1997 10  812.
 1998 03 684·
 1998 04 977.
 1998 08 190.
 1998 09 880.
 1998 10 611·
 1998 11 23
 1999 02  400·
 1999 03  38
 1999 04  990·
 1999 05  910·
 1999 06  222·
 1999 07  12
 1999 08  94
 1999 09  476·
 1999 10  406·
 1999 11  162.
 1999 12  851.
 2000 05 580.
 2000 06 954·
 2000 07 823.
 2000 08 343.
 2000 09 186·
 2000 10 103.
 2000 11 670.
 2000 12 290.
 2001 01  48
 2001 05  384·
 2001 06  524.
 2001 07  832.
 2001 08  912·
 2001 09  53
 2001 10  452.
 2002 08 343.
 2003 01  16
 2003 02  572·
 2003 07  762.
 2003 11  463.
 2003 12  174·
 2004 01 734·
 2004 02 21·
 2004 03 54.
 2004 05 142·
 2004 06 532·
 2004 07 65·
 2004 08 243·
 2004 09 511.
 2005 06  723·
 2005 07  933.
 2005 08  430·
 2005 09  961.
 2005 10  300.
 2006 06 95
 2006 10 221·
 2008 01 450·
 2008 02 530·
 2008 03 701.
 2009 06  510.
 2009 07  150.
 2009 08  910·
 2009 09  970.
 2009 10  430·
 2009 11  520.
 2009 12  202.
 2010 01 860.
 2010 02 340·
 2010 03 243.
 2010 04 400·
 2010 05 65
 2010 06 880.
 2010 07 260.
 2010 08 760.
 2010 09 943·
 2010 10 940·
 2010 11 760·
 2010 12 790.
 2011 01  520·
 2011 02  631.
 2011 03  201·
 2011 04  241·
 2011 05  471·
 2011 06  340·
 2011 07  251·
 2011 08  113.
 2011 09  113.
 2011 10  693.
 2011 11  860·
 2011 12  66
 2012 01 990.
 2012 02 570·
 2012 03 221·
 2012 04 401.
 2012 05 955.
 2012 06 105·
 2012 07 780·
 2012 08 7
 2012 09 30.
 2012 10 670.
 2012 11 220·
 2012 12 691.
 2013 01  570.
 2013 02  890.
 2013 03  49
 2013 04  500·
 2013 05  121.
 2013 06  660·
 2013 07  780·
 2013 08  00.
 2013 09  500·
 2013 10  100·
 2013 11  531.
 2013 12  96
 2014 01 792·
 2014 02 583·
 2014 03 420·
 2014 04 380·
 2014 05 280·
 2014 06 740·
 2014 07 412.
 2014 08 510.
 2014 09 562.
 2014 10 46
 2014 11 690.
 2014 12 851·
 2015 01  441.
 2015 02  860.
 2015 03  680.
 2015 04  161.
 2015 05  981·
 2015 06  331.
 2015 07  101.
 2015 08  441·
 2015 09  504.
 2015 10  490.
 2015 11  870·
 2015 12  940.
 2016 01 57
 2016 02 220·
 2016 03 190.
 2016 04 180.
 2016 05 12.
 2016 06 652.
 2016 07 500.
 2016 08 900.
 2016 09 870.
 2016 10 160.
 2016 11 500.
 2016 12 110·
 2017 01  480·
 2017 02  380.
 2017 03  110.
 2017 04  50.
 2017 05  400.


 2017 06  180·
 2017 07  540.
 2017 08  250.
 2017 09  45
 2017 10  701.
 2017 11  23
 2017 12  441.
 2018 01 700.
 2018 02 320.
 2018 03 872·
 2018 04 640.
 2018 05 460·
 2018 06 660.
 2018 07 390·
 2018 08 90.
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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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