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 Series Title: Employment Level: Agriculture and Related Industries, Unpaid Family Workers, 35-44 years, Women: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Yearly Chart  |  Excel file  |  Self-updating Excel file
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 1976 06 157·
 1976 07 6650·
 1976 08 3455·
 1976 09 2761.
 1976 10 8869·
 1976 11 6761·
 1976 12 1345.
 1977 01  635·
 1977 02  535·
 1977 03  2928·
 1977 04  5652.
 1977 05  4671·
 1977 06  179.
 1977 07  3483·
 1977 08  7463·
 1977 09  9248.
 1977 10  5254.
 1977 11  8862·
 1977 12  737·
 1978 01 1229.
 1978 02 5730.
 1978 03 2337·
 1978 04 1740·
 1978 05 152.
 1978 06 4355.
 1978 07 9577·
 1978 08 9252·
 1978 09 7744.
 1978 10 6054.
 1978 11 8744.
 1978 12 4438·
 1979 01  8620.
 1979 02  8325·
 1979 03  432·
 1979 04  1336·
 1979 05  9552·
 1979 06  1361·
 1979 07  7966·
 1979 08  6048.
 1979 09  9947.
 1979 10  7459.
 1979 11  6849·
 1979 12  7340.
 1980 01 1830.
 1980 02 1825.
 1980 03 5329·
 1980 04 6644·
 1980 05 9563.
 1980 06 2067.
 1980 07 4083·
 1980 08 7760.
 1980 09 055·
 1980 10 8057·
 1980 11 6146.
 1980 12 6737·
 1981 01  2733·
 1981 02  2342.
 1981 03  7334.
 1981 04  2641.
 1981 05  9438.
 1981 06  042·
 1981 07  5650.
 1981 08  6541·
 1981 09  4629.
 1981 10  8745.
 1981 11  1947·
 1981 12  2422.
 1982 01 5329·
 1982 02 8323.
 1982 03 9321·
 1982 04 6433·
 1982 05 742·
 1982 06 1455·
 1982 07 3455·
 1982 08 7456.
 1982 09 3044.
 1982 10 3144.
 1982 11 2343.
 1982 12 6725·
 1983 01  6321·
 1983 02  922.
 1983 03  6837·
 1983 04  8025·
 1983 05  7835·
 1983 06  4850.
 1983 07  145·
 1983 08  7641.
 1983 09  6736.
 1983 10  7340.
 1983 11  7733.
 1983 12  4331·
 1984 01 5021·
 1984 02 3617.
 1984 03 7827.
 1984 04 9533·
 1984 05 7142.
 1984 06 1151.
 1984 07 1158·
 1984 08 6857.
 1984 09 041.
 1984 10 9933·
 1984 11 932·
 1984 12 2734.
 1985 01  3034·
 1985 02  2530.
 1985 03  2648·
 1985 04  5830·
 1985 05  8047·
 1985 06  3941·
 1985 07  4640.
 1985 08  7528·
 1985 09  9625·
 1985 10  1820·
 1985 11  7419·
 1985 12  1619·
 1986 01 4519.
 1986 02 6115.
 1986 03 4232.
 1986 04 4321·
 1986 05 2230·
 1986 06 9441.
 1986 07 837.
 1986 08 4426·
 1986 09 4611.
 1986 10 6722·
 1986 11 5129·
 1986 12 3317.
 1987 01  6123.
 1987 02  5615·
 1987 03  8017.
 1987 04  4617·
 1987 05  3719·
 1987 06  6016.
 1987 07  2615.
 1987 08  4821·
 1987 09  6714·
 1987 10  619.
 1987 11  4634.
 1987 12  2520·
 1988 01 7122.
 1988 02 4326·
 1988 03 2016.
 1988 04 9214·
 1988 05 9230·
 1988 06 4825.
 1988 07 5624.
 1988 08 8523.
 1988 09 113·
 1988 10 2023.
 1988 11 8620·
 1988 12 6818.
 1989 01  9111.
 1989 02  8616.
 1989 03  6525.
 1989 04  2817·
 1989 05  8128·
 1989 06  9431.
 1989 07  7728·
 1989 08  7826.
 1989 09  1519·
 1989 10  2119·
 1989 11  2622.
 1989 12  5722.
 1990 01 638.
 1990 02 677.
 1990 03 4613.
 1990 04 2717.
 1990 05 1827·
 1990 06 5825.
 1990 07 9220·
 1990 08 7620·
 1990 09 025·
 1990 10 4320.
 1990 11 4616.
 1990 12 179·
 1991 01  5419.
 1991 02  9917.
 1991 03  1618.
 1991 04  88
 1991 05  4729·
 1991 06  2519.
 1991 07  3123.
 1991 08  5113·
 1991 09  7416.
 1991 10  4812.
 1991 11  5010.
 1991 12  958.
 1992 01 559.
 1992 02 1713.
 1992 03 548·
 1992 04 3215·
 1992 05 3312·
 1992 06 736·
 1992 07 4925·
 1992 08 126.
 1992 09 7814·
 1992 10 2018.
 1992 11 6718.
 1992 12 644·
 1993 01  8412.
 1993 02  8016.
 1993 03  6522·
 1993 04  1016·
 1993 05  7022.
 1993 06  3933·
 1993 07  2523·
 1993 08  5017.
 1993 09  7924.
 1993 10  7118.
 1993 11  5213.
 1993 12  2316.
 1994 01 822.
 1994 02 762.
 1994 03 794·
 1994 04 92
 1994 05 727.
 1994 06 818·
 1994 07 6210·
 1994 08 454·
 1994 09 692·
 1994 10 351.
 1994 11 832·
 1994 12 953·
 1995 01  162·
 1995 02  142.
 1995 03  493·
 1995 04  79
 1995 05  836.
 1995 06  196.
 1995 07  9110·
 1995 08  604.
 1995 09  641.
 1995 10  741.
 1995 11  660·
 1995 12  271·
 1996 01 783.
 1996 02 301·
 1996 03 551.
 1996 04 912.
 1996 05 696·
 1996 06 636·
 1996 07 655.
 1996 08 927.
 1996 09 75.
 1996 10 73
 1996 11 284·
 1996 12 924·
 1997 01  852.
 1997 02  842.
 1997 03  12.
 1997 04  792·
 1997 05  225.
 1997 06  49
 1997 07  6510.
 1997 08  657·
 1997 09  644·
 1997 10  424.
 1997 11  266·
 1997 12  894·
 1998 01 78
 1998 02 634.
 1998 03 163.
 1998 05 145.
 1998 06 592·
 1998 07 386.
 1998 08 937.
 1998 09 271.
 1998 10 261·
 1998 11 175·
 1998 12 373·
 1999 02  411.
 1999 03  244.
 1999 04  761·
 1999 05  561.
 1999 06  943·
 1999 07  2113·
 1999 08  1511.
 1999 09  8012·
 1999 10  5016·
 1999 11  125.
 1999 12  597·
 2000 01 674·
 2000 02 952·
 2000 03 152.
 2000 04 593.
 2000 05 986·
 2000 07 443·
 2000 08 753.
 2001 02  900·
 2001 03  800.
 2001 04  332·
 2001 05  622.
 2001 07  533·
 2001 09  441·
 2001 10  263·
 2001 12  682.
 2002 02 73
 2002 03 473·
 2002 04 103.
 2002 05 143.
 2002 07 0
 2002 08 710·
 2002 09 992·
 2002 10 435·
 2002 11 95.
 2002 12 23
 2003 01  306·
 2003 02  253·
 2003 03  23.
 2003 04  331.
 2003 05  660.
 2003 06  530.
 2003 07  41.
 2003 08  590.
 2003 09  95
 2003 10  471·
 2003 11  640·
 2003 12  831.
 2004 01 311·
 2004 02 521·
 2004 03 591·
 2004 06 100.
 2004 07 102.
 2004 08 352·
 2004 09 882.
 2004 10 732.
 2005 01  962.
 2005 02  925.
 2005 03  783.
 2005 04  28
 2005 07  763·
 2005 08  411·
 2005 10  781·
 2005 11  571·
 2005 12  65
 2006 01 273·
 2006 05 642·
 2006 06 674·
 2006 07 984.
 2006 08 180·
 2007 01  362.
 2007 02  893.
 2007 03  403.
 2007 04  93·
 2007 05  201·
 2007 06  790·
 2007 07  787.
 2007 08  190·
 2007 09  664·
 2007 11  200.
 2007 12  260·
 2008 01 920.
 2008 02 492·
 2008 04 18
 2008 05 201.
 2008 12 984·
 2009 01  703.
 2009 06  50·
 2009 07  240·
 2009 08  300·
 2009 09  540·
 2009 10  37
 2009 11  260·
 2009 12  71·
 2010 01 52
 2010 02 960·
 2010 03 390.
 2010 04 75
 2010 05 393.
 2010 06 880.
 2010 07 03.
 2010 08 00·
 2010 09 150.
 2010 10 462·
 2010 11 73
 2010 12 792.
 2011 01  62·
 2011 02  260.
 2011 03  453.
 2011 04  301.
 2011 05  620·
 2011 06  90.
 2011 07  290·
 2011 08  980.
 2011 09  592.
 2011 10  3
 2011 11  632.
 2011 12  503.
 2012 01 97
 2012 02 383.
 2012 03 113·
 2012 04 823.
 2012 05 13.
 2012 06 720·
 2012 07 590.
 2012 08 130.
 2012 09 220·
 2012 10 860.
 2012 11 210.
 2012 12 873.
 2013 01  352·
 2013 02  863.
 2013 03  353.
 2013 04  733·
 2013 05  400.
 2013 06  50.
 2013 07  630·
 2013 08  640.
 2013 09  633·
 2013 10  990.
 2013 11  940·
 2013 12  810.
 2014 01 550.
 2014 02 501.
 2014 03 400·
 2014 04 67
 2014 05 903·
 2014 06 640·
 2014 07 400.
 2014 08 920·
 2014 09 703·
 2014 10 730·
 2014 11 560.
 2014 12 490.
 2015 01  190·
 2015 02  344·
 2015 03  757·
 2015 04  599.
 2015 05  877·
 2015 06  284·
 2015 07  12
 2015 08  640·
 2015 09  510·
 2015 10  610.
 2015 11  3
 2015 12  344·
 2016 01 11
 2016 02 661.
 2016 03 124.
 2016 04 630.
 2016 05 910.
 2016 06 00.
 2016 07 272.
 2016 08 71


 2016 09 430.
 2016 10 430·
 2016 11 600·
 2016 12 1
 2017 01  42
 2017 02  31·
 2017 03  504.
 2017 04  23
 2017 05  883.
 2017 06  104.
 2017 07  580.
 2017 08  311.
 2017 09  70·
 2017 10  230·
 2017 11  740.
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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, Women: 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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