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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 07 494.
 1976 08 923.
 1976 09 832·
 1976 10 642.
 1976 11 992·
 1976 12 537·
 1977 01  952.
 1977 02  252·
 1977 03  205·
 1977 04  183.
 1977 05  154·
 1977 06  911·
 1977 07  650·
 1977 08  701.
 1977 09  540·
 1977 11  51·
 1977 12  8
 1978 01 151.
 1978 02 512.
 1978 03 382·
 1978 06 502·
 1978 07 850·
 1978 08 690.
 1978 09 843.
 1978 10 162.
 1978 12 35
 1979 01  951·
 1979 03  607.
 1979 04  566.
 1979 05  493·
 1979 06  444·
 1979 07  135.
 1979 08  470·
 1979 09  320.
 1979 10  513.
 1980 03 101.
 1980 04 886·
 1980 05 175·
 1980 06 824·
 1980 07 463.
 1980 08 42·
 1980 09 592.
 1980 10 222.
 1980 11 403.
 1980 12 473·
 1981 01  412.
 1981 02  861·
 1981 03  363·
 1981 04  914.
 1981 05  691.
 1981 06  105.
 1981 07  41·
 1981 08  373.
 1981 09  754.
 1981 10  591·
 1981 11  37
 1981 12  10
 1982 01 152.
 1982 02 209·
 1982 03 545·
 1982 04 612·
 1982 05 711·
 1982 06 53·
 1982 10 12·
 1982 12 651·
 1983 06  501.
 1984 01 534.
 1984 02 453.
 1984 03 232·
 1984 04 832·
 1984 05 261.
 1984 06 811.
 1984 09 592.
 1984 12 272.
 1985 01  132·
 1985 03  296·
 1985 04  244.
 1985 05  642·
 1985 07  26
 1985 08  314.
 1985 10  952.
 1985 11  03·
 1986 01 31.
 1986 03 591.
 1986 06 701·
 1986 07 671·
 1986 08 8
 1986 09 4
 1986 10 754.
 1986 11 212.
 1986 12 271·
 1987 01  883.
 1987 02  621.
 1987 04  454·
 1987 05  745·
 1987 06  533·
 1987 07  41.
 1987 08  441.
 1987 09  871.
 1987 10  694.
 1987 11  36.
 1987 12  515.
 1988 01 292·
 1988 02 312.
 1988 04 842.
 1988 05 226.
 1988 06 8710·
 1988 07 572.
 1988 08 982·
 1988 09 391·
 1988 10 742.
 1988 11 912·
 1988 12 193.
 1989 01  84.
 1989 02  292·
 1989 03  3
 1989 04  4810·
 1989 05  618.
 1989 06  1410·
 1989 07  862·
 1989 08  111·
 1989 09  547.
 1989 10  171.
 1990 02 612.
 1990 03 582·
 1990 04 71
 1990 05 522·
 1990 06 701·
 1990 09 642·
 1990 10 15
 1990 12 552.
 1991 02  845.
 1991 03  292·
 1991 04  213.
 1991 06  892·
 1991 07  95
 1991 08  803·
 1991 11  44
 1991 12  442.
 1992 01 243.
 1992 02 673·
 1992 03 653.
 1992 04 313.
 1992 05 151·
 1992 09 642.
 1992 10 924·
 1992 11 887.
 1992 12 371.
 1993 01  722.
 1993 02  573.
 1993 03  792·
 1993 04  833.
 1993 05  175·
 1993 06  152.
 1993 07  911.
 1993 08  735·
 1993 09  509·
 1994 01 482.
 1994 02 37
 1994 08 511·
 1994 09 441.
 1994 10 641·
 1994 11 55
 1994 12 872·
 1995 01  11.
 1995 02  931·
 1995 03  86.
 1995 04  746·
 1995 05  476.
 1995 06  938.
 1995 07  845·
 1995 08  327·
 1995 09  314.
 1995 10  443.
 1995 11  962.
 1995 12  44·
 1996 01 302.
 1996 02 542.
 1996 03 812.
 1996 04 603·
 1996 05 422.
 1996 06 552.
 1996 07 21.
 1996 08 943·
 1996 11 945.
 1996 12 20·
 1997 01  485.
 1997 04  252·
 1997 05  373·
 1997 06  783·
 1997 07  31
 1997 08  974.
 1997 09  455·
 1997 10  892.
 1998 03 894·
 1998 04 80
 1998 08 190.
 1998 09 670.
 1998 10 861·
 1998 11 67
 1999 02  850.
 1999 03  680·
 1999 04  80·
 1999 05  780·
 1999 06  922·
 1999 07  754·
 1999 08  696·
 1999 09  576.
 1999 10  16
 1999 11  932·
 1999 12  61.
 2000 05 720.
 2000 06 584·
 2000 07 553.
 2000 08 833.
 2000 09 196·
 2000 10 423.
 2000 11 160·
 2000 12 880·
 2001 01  160.
 2001 05  204·
 2001 06  604.
 2001 07  332·
 2001 08  72·
 2001 09  672·
 2001 10  912·
 2002 08 573.
 2003 01  622.
 2003 02  832.
 2003 07  432.
 2003 11  213.
 2003 12  754.
 2004 01 934·
 2004 02 711.
 2004 03 144.
 2004 05 642.
 2004 06 482·
 2004 07 575.
 2004 08 503·
 2004 09 741.
 2005 06  233·
 2005 07  93·
 2005 08  650·
 2005 09  751·
 2005 10  190·
 2006 06 562·
 2006 10 231·
 2008 01 59
 2008 02 610.
 2008 03 571.
 2009 06  110.
 2009 07  470.
 2009 08  990·
 2009 09  930.
 2009 10  430·
 2009 11  820·
 2009 12  92.
 2010 01 700.
 2010 02 570·
 2010 03 343.
 2010 04 920.
 2010 05 21
 2010 06 150.
 2010 07 970·
 2010 08 72
 2010 09 13·
 2010 10 4
 2010 11 89
 2010 12 00.
 2011 01  920.
 2011 02  391.
 2011 03  561·
 2011 04  511.
 2011 05  11·
 2011 06  570.
 2011 07  661.
 2011 08  263.
 2011 09  603.
 2011 10  213·
 2011 11  130.
 2011 12  501.
 2012 01 250·
 2012 02 180.
 2012 03 171.
 2012 04 741·
 2012 05 795.
 2012 06 625·
 2012 07 210·
 2012 08 720·
 2012 09 260·
 2012 10 900·
 2012 11 95
 2012 12 461·
 2013 01  00.
 2013 02  660·
 2013 03  330·
 2013 04  210.
 2013 05  571.
 2013 06  770.
 2013 07  540.
 2013 08  470·
 2013 09  78
 2013 10  37
 2013 11  31.
 2013 12  993·
 2014 01 712.
 2014 02 82
 2014 03 47
 2014 04 790·
 2014 05 660.
 2014 06 770.
 2014 07 822.
 2014 08 100·
 2014 09 212.
 2014 10 80.
 2014 11 270.
 2014 12 441·
 2015 01  161.
 2015 02  890·
 2015 03  250.
 2015 04  561.
 2015 05  59
 2015 06  57
 2015 07  461.
 2015 08  471·
 2015 09  824.
 2015 10  76
 2015 11  84
 2015 12  410.
 2016 01 410.
 2016 02 340.
 2016 03 590.
 2016 04 900.
 2016 05 172·
 2016 06 432·
 2016 07 130·
 2016 08 690.
 2016 09 170.
 2016 10 41


 2016 11 180.
 2016 12 770·
 2017 01  74
 2017 02  910.
 2017 03  650.
 2017 04  410·
 2017 05  43
 2017 06  810·
 2017 07  760·
 2017 08  100·
 2017 09  61·
 2017 10  241·
 2017 11  930·
 2017 12  611·
 2018 01 690.
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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
   Transform this series  |  Display series in COPY/PASTE format  |  More series like this one

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