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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 4656·
 1976 07 1354·
 1976 08 259.
 1976 09 6563·
 1976 10 8071·
 1976 11 2462·
 1976 12 8053.
 1977 01  5738·
 1977 02  4838.
 1977 03  233·
 1977 04  2755·
 1977 05  1775.
 1977 06  379·
 1977 07  2983·
 1977 08  5764.
 1977 09  8848·
 1977 10  1854·
 1977 11  1263.
 1977 12  738.
 1978 01 4030.
 1978 02 9432.
 1978 03 8240.
 1978 04 4140.
 1978 05 6752.
 1978 06 5757.
 1978 07 9577·
 1978 08 4652·
 1978 09 8746.
 1978 10 5757·
 1978 11 3444.
 1978 12 3541·
 1979 01  4620.
 1979 02  7025·
 1979 03  540·
 1979 04  4642·
 1979 05  1255.
 1979 06  9565.
 1979 07  4071·
 1979 08  4248·
 1979 09  8048·
 1979 10  5962·
 1979 11  9549.
 1979 12  1140.
 1980 01 6830·
 1980 02 1125.
 1980 03 5230·
 1980 04 6649.
 1980 05 2068.
 1980 06 2771·
 1980 07 1785.
 1980 08 4462.
 1980 09 758·
 1980 10 859·
 1980 11 2349·
 1980 12 840·
 1981 01  2135.
 1981 02  7843.
 1981 03  2638·
 1981 04  4744·
 1981 05  8339.
 1981 06  8947.
 1981 07  751·
 1981 08  7344.
 1981 09  3633.
 1981 10  1547·
 1981 11  7448.
 1981 12  2425·
 1982 01 4931·
 1982 02 5732·
 1982 03 5725.
 1982 04 6335.
 1982 05 1743·
 1982 06 4058·
 1982 07 1455.
 1982 08 7857.
 1982 09 5844·
 1982 10 1546.
 1982 11 2642·
 1982 12 8227.
 1983 01  1720·
 1983 02  5721.
 1983 03  037·
 1983 04  1325.
 1983 05  6335.
 1983 06  6750·
 1983 07  6745·
 1983 08  3341.
 1983 09  9036.
 1983 10  7040.
 1983 11  8434.
 1983 12  3131·
 1984 01 1826.
 1984 02 1620.
 1984 03 3330·
 1984 04 1934.
 1984 05 9044·
 1984 06 8052·
 1984 07 2058.
 1984 08 3557·
 1984 09 7543.
 1984 10 6433.
 1984 11 7731.
 1984 12 4236·
 1985 01  6836.
 1985 02  9229·
 1985 03  6155·
 1985 04  2933.
 1985 05  8849·
 1985 06  1541·
 1985 07  5244·
 1985 08  732·
 1985 09  7824·
 1985 10  823·
 1985 11  5922·
 1985 12  1518·
 1986 01 921.
 1986 02 7214.
 1986 03 1233·
 1986 04 1621·
 1986 05 7430·
 1986 06 3242.
 1986 07 6938.
 1986 08 9827.
 1986 09 9216.
 1986 10 3826.
 1986 11 1031·
 1986 12 7318.
 1987 01  826·
 1987 02  6616·
 1987 03  4318·
 1987 04  7921.
 1987 05  9124·
 1987 06  1719.
 1987 07  9916.
 1987 08  8021.
 1987 09  3414.
 1987 10  1524·
 1987 11  3440.
 1987 12  6325.
 1988 01 5725.
 1988 02 1128.
 1988 03 3116.
 1988 04 4016·
 1988 05 436·
 1988 06 8035·
 1988 07 9626.
 1988 08 5125·
 1988 09 4413·
 1988 10 2325.
 1988 11 6022.
 1988 12 5821.
 1989 01  7215·
 1989 02  6519·
 1989 03  8134.
 1989 04  4826·
 1989 05  635.
 1989 06  5741·
 1989 07  3930·
 1989 08  3526·
 1989 09  9126.
 1989 10  7320·
 1989 11  4322·
 1989 12  5722·
 1990 01 968.
 1990 02 159.
 1990 03 2215·
 1990 04 7519·
 1990 05 1429.
 1990 06 827·
 1990 07 3420·
 1990 08 7920.
 1990 09 6627·
 1990 10 222.
 1990 11 6116·
 1990 12 8211·
 1991 01  9419.
 1991 02  7222·
 1991 03  920·
 1991 04  2012·
 1991 05  6929·
 1991 06  1921·
 1991 07  1028.
 1991 08  5716·
 1991 09  8517·
 1991 10  6913.
 1991 11  2012·
 1991 12  8210·
 1992 01 6012.
 1992 02 7116·
 1992 03 2111.
 1992 04 618·
 1992 05 3813·
 1992 06 136·
 1992 07 1925·
 1992 08 6726·
 1992 09 9016·
 1992 10 6022·
 1992 11 4824·
 1992 12 295·
 1993 01  913·
 1993 02  7220·
 1993 03  6224.
 1993 04  8019·
 1993 05  1426.
 1993 06  8935.
 1993 07  4324·
 1993 08  3122·
 1993 09  4933·
 1993 10  8517·
 1993 11  9914·
 1993 12  2216·
 1994 01 834.
 1994 02 612.
 1994 03 614.
 1994 04 157·
 1994 05 12
 1994 06 438·
 1994 07 8510.
 1994 08 986.
 1994 09 534.
 1994 10 811.
 1994 11 542·
 1994 12 845·
 1995 01  503·
 1995 02  493.
 1995 03  739.
 1995 04  1114·
 1995 05  7413.
 1995 06  4914.
 1995 07  7515·
 1995 08  4112·
 1995 09  186.
 1995 10  75.
 1995 11  163.
 1995 12  635·
 1996 01 15.
 1996 02 713·
 1996 03 773.
 1996 04 895.
 1996 05 687.
 1996 06 197·
 1996 07 666.
 1996 08 5810.
 1996 09 874.
 1996 10 494.
 1996 11 149·
 1996 12 314.
 1997 01  538.
 1997 02  881.
 1997 03  782·
 1997 04  984·
 1997 05  858·
 1997 06  8610·
 1997 07  3913.
 1997 08  7111·
 1997 09  279.
 1997 10  186·
 1997 11  46.
 1997 12  883·
 1998 01 474·
 1998 02 854·
 1998 03 47.
 1998 04 117·
 1998 05 425.
 1998 06 122·
 1998 07 97
 1998 08 297.
 1998 09 281·
 1998 10 502·
 1998 11 647.
 1998 12 553.
 1999 02  511.
 1999 03  735·
 1999 04  111.
 1999 05  261·
 1999 06  805.
 1999 07  8317·
 1999 08  7018·
 1999 09  618·
 1999 10  922.
 1999 11  4
 1999 12  988.
 2000 01 814.
 2000 02 572·
 2000 03 872.
 2000 04 763.
 2000 05 66
 2000 06 674.
 2000 07 87.
 2000 08 116·
 2000 09 986.
 2000 10 103.
 2000 11 670.
 2000 12 360·
 2001 01  400.
 2001 02  800·
 2001 03  880.
 2001 04  52·
 2001 05  796.
 2001 06  954·
 2001 07  245.
 2001 08  22·
 2001 09  293·
 2001 10  995.
 2001 12  482·
 2002 02 320·
 2002 03 283·
 2002 04 633.
 2002 05 623·
 2002 07 274.
 2002 08 383.
 2002 09 792.
 2002 10 905·
 2002 11 445.
 2002 12 485.
 2003 01  687.
 2003 02  844·
 2003 03  653.
 2003 04  691·
 2003 05  720.
 2003 06  180·
 2003 07  963·
 2003 08  410·
 2003 09  632.
 2003 10  941.
 2003 11  693.
 2003 12  265.
 2004 01 325.
 2004 02 35
 2004 03 405·
 2004 05 122·
 2004 06 12.
 2004 07 937·
 2004 08 925·
 2004 09 122·
 2004 10 122·
 2005 01  442.
 2005 02  305·
 2005 03  633·
 2005 04  352.
 2005 06  873.
 2005 07  866·
 2005 08  291.
 2005 09  64
 2005 10  48
 2005 11  181·
 2005 12  971·
 2006 01 183.
 2006 05 772.
 2006 06 66.
 2006 07 814·
 2006 08 420.
 2006 10 491·
 2007 01  582·
 2007 02  18
 2007 03  43·
 2007 04  663.
 2007 05  41·
 2007 06  710·
 2007 07  997·
 2007 08  530.
 2007 09  24·
 2007 11  280.
 2007 12  460.
 2008 01 591·
 2008 02 342.
 2008 03 21.
 2008 04 892.
 2008 05 601.
 2008 12 54·
 2009 01  313·
 2009 06  960.
 2009 07  570.
 2009 08  48
 2009 09  781·
 2009 10  632.
 2009 11  750·
 2009 12  183·
 2010 01 300.
 2010 02 80·
 2010 03 653.
 2010 04 990·
 2010 05 13·
 2010 06 760·
 2010 07 13.
 2010 08 96
 2010 09 283·
 2010 10 36
 2010 11 852.
 2010 12 412.
 2011 01  74
 2011 02  811·
 2011 03  414.
 2011 04  912.
 2011 05  271·
 2011 06  310·
 2011 07  201.
 2011 08  283·
 2011 09  15·
 2011 10  305.
 2011 11  97
 2011 12  573.
 2012 01 320.
 2012 02 473.
 2012 03 744·
 2012 04 11
 2012 05 858·
 2012 06 775.
 2012 07 740·
 2012 08 46
 2012 09 460.
 2012 10 380·
 2012 11 490·
 2012 12 443.
 2013 01  282.
 2013 02  753.
 2013 03  743·
 2013 04  123·
 2013 05  711.
 2013 06  560.
 2013 07  49
 2013 08  80
 2013 09  353.
 2013 10  770.
 2013 11  01.
 2013 12  73.
 2014 01 102·
 2014 02 554·
 2014 03 770.
 2014 04 73
 2014 05 83·
 2014 06 360·
 2014 07 552·
 2014 08 860.
 2014 09 675.
 2014 10 880.
 2014 11 360·
 2014 12 761.
 2015 01  501.
 2015 02  54·
 2015 03  43
 2015 04  09·
 2015 05  458.
 2015 06  75·
 2015 07  292.
 2015 08  411·
 2015 09  644.
 2015 10  380.
 2015 11  670.
 2015 12  44.
 2016 01 470·
 2016 02 661.
 2016 03 594.
 2016 04 220.
 2016 05 542.
 2016 06 872·
 2016 07 302.
 2016 08 500·
 2016 09 76
 2016 10 190.
 2016 11 290.
 2016 12 71


 2017 01  230.
 2017 02  61.
 2017 03  344·
 2017 04  923·
 2017 05  353·
 2017 06  174.
 2017 07  430.
 2017 08  431.
 2017 09  73
 2017 10  481.
 2017 11  830.
 2017 12  821·
 2018 01 270·
 2018 02 150·
 2018 03 42.
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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

Unemployment data for every county in the U.S..
Click for Illinois counties, then follow the example for your state

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