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 Series Title: Employment Level: Agriculture and Related Industries, Unpaid Family Workers, 20-24 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 5850.
 1976 07 7447.
 1976 08 5039.
 1976 09 3732.
 1976 10 1324·
 1976 11 5721.
 1976 12 4919·
 1977 01  119.
 1977 02  419·
 1977 03  716.
 1977 04  1922·
 1977 05  3337·
 1977 06  8058.
 1977 07  633.
 1977 08  7038·
 1977 09  7625.
 1977 10  1710·
 1977 11  6022·
 1977 12  4320·
 1978 01 9921·
 1978 02 1511·
 1978 03 216.
 1978 04 9822.
 1978 05 9831.
 1978 06 054.
 1978 07 8754.
 1978 08 2538.
 1978 09 9127.
 1978 10 2225·
 1978 11 9820.
 1978 12 3621.
 1979 01  2123·
 1979 02  5716.
 1979 03  4122·
 1979 04  6927·
 1979 05  5944·
 1979 06  448.
 1979 07  4852·
 1979 08  8747.
 1979 09  9923.
 1979 10  8927.
 1979 11  7533·
 1979 12  7824.
 1980 01 5821.
 1980 02 6421.
 1980 03 325.
 1980 04 5427·
 1980 05 8331·
 1980 06 241.
 1980 07 4139·
 1980 08 5435.
 1980 09 4128.
 1980 10 436·
 1980 11 1930.
 1980 12 4019·
 1981 01  2818.
 1981 02  9626·
 1981 03  9322.
 1981 04  130.
 1981 05  6127.
 1981 06  2937·
 1981 07  4734·
 1981 08  4938·
 1981 09  8627.
 1981 10  7732·
 1981 11  8525.
 1981 12  2225.
 1982 01 7132·
 1982 02 4033.
 1982 03 4027.
 1982 04 8322.
 1982 05 1022·
 1982 06 4634·
 1982 07 6945.
 1982 08 2037.
 1982 09 2446.
 1982 10 4327.
 1982 11 5320·
 1982 12 4624.
 1983 01  5522·
 1983 02  715·
 1983 03  9828·
 1983 04  9832.
 1983 05  7334·
 1983 06  3845.
 1983 07  3751.
 1983 08  4036·
 1983 09  7228·
 1983 10  6330·
 1983 11  2620·
 1983 12  6026·
 1984 01 7123·
 1984 02 3113.
 1984 03 4711.
 1984 04 7013·
 1984 05 1528.
 1984 06 1735.
 1984 07 643·
 1984 08 831.
 1984 09 7220·
 1984 10 2310.
 1984 11 3515.
 1984 12 3715·
 1985 01  3715.
 1985 02  7320·
 1985 03  9023.
 1985 04  4522·
 1985 05  2822·
 1985 06  1733.
 1985 07  5428·
 1985 08  4631·
 1985 09  9125·
 1985 10  3319·
 1985 11  3315·
 1985 12  7613·
 1986 01 948.
 1986 02 188.
 1986 03 587·
 1986 04 9915.
 1986 05 3014.
 1986 06 016·
 1986 07 8622.
 1986 08 227.
 1986 09 2115·
 1986 10 2817.
 1986 11 9918·
 1986 12 99
 1987 01  813.
 1987 02  789·
 1987 03  412.
 1987 04  276.
 1987 05  6316.
 1987 06  5020.
 1987 07  3115·
 1987 08  4926·
 1987 09  7810·
 1987 10  705.
 1987 11  3912·
 1987 12  546.
 1988 01 733·
 1988 02 884.
 1988 03 713·
 1988 04 5415·
 1988 05 9213·
 1988 06 7913.
 1988 07 4413·
 1988 08 8719.
 1988 09 4
 1988 10 4411·
 1988 11 807·
 1988 12 1510.
 1989 01  410·
 1989 02  810·
 1989 03  7316·
 1989 04  278.
 1989 05  103.
 1989 06  2219·
 1989 07  411·
 1989 08  3619·
 1989 09  668.
 1989 10  6012.
 1989 11  799·
 1989 12  7915.
 1990 01 435.
 1990 02 2411·
 1990 03 303·
 1990 04 203.
 1990 05 337·
 1990 06 397.
 1990 07 1414·
 1990 08 4615.
 1990 09 562.
 1990 10 5411.
 1990 11 137.
 1990 12 708.
 1991 01  57
 1991 02  468·
 1991 03  329.
 1991 04  30
 1991 05  48.
 1991 06  1515·
 1991 07  516·
 1991 08  9013.
 1991 09  9110.
 1991 10  879·
 1991 11  878.
 1991 12  363.
 1992 01 383.
 1992 02 118.
 1992 03 608·
 1992 04 816·
 1992 05 897·
 1992 06 6316·
 1992 07 3010·
 1992 08 6514.
 1992 09 1214·
 1992 10 4310.
 1992 11 3020·
 1992 12 492.
 1993 01  37·
 1993 02  788.
 1993 03  1610.
 1993 04  217.
 1993 05  7913.
 1993 06  1613.
 1993 07  7011·
 1993 08  9518·
 1993 09  864.
 1993 10  343.
 1993 11  985.
 1993 12  82·
 1994 01 9315·
 1994 02 339.
 1994 03 313.
 1994 04 236.
 1994 05 9311.
 1994 06 369.
 1994 07 289·
 1994 08 2713·
 1994 09 68.
 1994 10 964.
 1994 11 687.
 1994 12 354.
 1995 01  756.
 1995 02  863.
 1995 03  59
 1995 04  847·
 1995 05  718.
 1995 06  83·
 1995 07  339.
 1995 08  3611.
 1995 09  874.
 1995 10  874.
 1995 11  463.
 1995 12  795·
 1996 01 428.
 1996 02 746.
 1996 03 797.
 1996 04 284.
 1996 05 812.
 1996 06 434·
 1996 07 4015.
 1996 08 18
 1996 09 7211.
 1996 10 950.
 1996 11 605·
 1996 12 148·
 1997 01  96·
 1997 03  567.
 1997 04  9510·
 1997 05  25·
 1997 06  133.
 1997 07  766.
 1997 08  286·
 1997 09  977.
 1997 10  2711·
 1997 11  304.
 1997 12  656·
 1998 01 36
 1998 04 191.
 1998 05 195·
 1998 06 379·
 1998 07 818.
 1998 08 866·
 1998 09 685.
 1998 10 25.
 1998 11 2116.
 1998 12 449.
 1999 01  276.
 1999 02  404·
 1999 03  682·
 1999 04  392.
 1999 05  723·
 1999 06  592.
 1999 07  616.
 1999 08  405.
 1999 09  46.
 1999 10  904.
 1999 11  638·
 1999 12  404.
 2000 01 479·
 2000 02 9012·
 2000 03 607·
 2000 04 606·
 2000 05 526.
 2000 06 407.
 2000 07 67
 2000 08 424.
 2000 09 955·
 2000 10 483·
 2000 11 216·
 2000 12 576·
 2001 01  75
 2001 02  446·
 2001 03  846·
 2001 04  9914·
 2001 05  1912·
 2001 06  857·
 2001 09  461.
 2001 10  852.
 2001 11  763.
 2001 12  537·
 2002 01 1812.
 2002 03 622·
 2002 04 222.
 2002 05 5510.
 2002 06 38
 2002 07 972·
 2002 08 58
 2002 09 221·
 2002 10 700·
 2003 01  864.
 2003 02  94.
 2003 03  125.
 2003 04  23.
 2003 05  460.
 2003 06  248.
 2003 07  46·
 2003 08  451·
 2003 09  230.
 2003 10  803·
 2003 11  73.
 2003 12  393.
 2004 02 855.
 2004 04 773·
 2004 05 526.
 2004 06 469.
 2004 07 261.
 2004 08 416·
 2004 09 9510·
 2004 10 548.
 2004 11 665.
 2004 12 217·
 2005 01  18
 2005 03  756·
 2005 04  494.
 2005 05  934.
 2005 06  2810·
 2005 07  4812.
 2005 08  442·
 2005 09  584.
 2005 10  578.
 2005 11  368·
 2005 12  454.
 2006 01 414.
 2006 02 6011·
 2006 03 264·
 2006 04 726·
 2006 05 923.
 2006 06 2011·
 2006 07 327.
 2006 08 67
 2006 09 866.
 2006 10 442.
 2006 11 918.
 2007 02  13·
 2007 03  257·
 2007 04  626·
 2007 05  664·
 2007 06  687·
 2007 07  3310.
 2007 08  321.
 2007 11  452·
 2008 04 874.
 2008 05 611.
 2008 06 3511.
 2008 07 411.
 2008 08 14.
 2008 09 854.
 2008 10 780·
 2009 01  914.
 2009 02  817.
 2009 03  412·
 2009 04  939·
 2009 05  60
 2009 06  20
 2009 07  449·
 2009 08  365·
 2009 09  340.
 2009 10  370.
 2009 11  551.
 2009 12  883·
 2010 01 265·
 2010 02 763.
 2010 03 132·
 2010 04 574·
 2010 05 756·
 2010 06 810.
 2010 07 1911.
 2010 08 746.
 2010 09 445.
 2010 10 255·
 2010 11 979·
 2010 12 965·
 2011 01  193·
 2011 02  471.
 2011 03  981·
 2011 04  40·
 2011 05  143·
 2011 06  1812.
 2011 07  97
 2011 08  515.
 2011 09  6812·
 2011 10  77.
 2011 11  9512.
 2011 12  310.
 2012 01 42
 2012 02 86·
 2012 03 1712·
 2012 04 389·
 2012 05 2512·
 2012 06 415.
 2012 07 1416.
 2012 08 87.
 2012 09 2912·
 2012 10 501.
 2012 11 613·
 2012 12 48
 2013 01  9311.
 2013 02  3
 2013 03  588·
 2013 04  883.
 2013 05  800·
 2013 06  965·
 2013 07  314.
 2013 08  876.
 2013 09  765·
 2013 10  465.
 2013 11  291.
 2013 12  251.
 2014 01 960.
 2014 02 982.
 2014 03 30
 2014 04 90·
 2014 05 772.
 2014 06 222·
 2014 07 322.
 2014 08 714·
 2014 09 822·
 2014 10 112·
 2014 11 622·
 2014 12 683.
 2015 01  992.
 2015 02  852.
 2015 03  690·
 2015 04  800·
 2015 05  402.
 2015 06  8812.
 2015 07  299.
 2015 08  1510·
 2015 09  458.
 2015 10  884.
 2015 11  433·
 2015 12  57.
 2016 01 748.
 2016 02 810.
 2016 03 357.
 2016 04 51·
 2016 05 173·
 2016 06 853·
 2016 07 572·
 2016 08 980·
 2016 09 873.
 2016 10 447·
 2016 11 8310.
 2016 12 904.
 2017 01  203·
 2017 02  27


 2017 03  151.
 2017 04  130.
 2017 05  814.
 2017 06  292·
 2017 07  77
 2017 08  241·
 2017 09  5614·
 2017 10  6914.
 2017 11  196.
 2017 12  47.
 2018 01 601·
 2018 02 902·
 2018 03 183.
 2018 04 592·
 2018 05 29
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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, 20-24 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

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