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 Series Title: Employment Level: Nonagriculture, Unpaid Family Workers, 45-54 years, Men: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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 2012 04 77·
 2012 03 985·
 2012 02 3812·
 2012 01 010·
 2011 12  784·
 2011 11  704.
 2011 10  760.
 2011 09  254.
 2011 08  284·
 2011 07  537.
 2011 06  276.
 2011 05  62
 2011 04  80·
 2011 03  293·
 2011 02  43·
 2011 01  540·
 2010 12 923.
 2010 11 40.
 2010 10 45
 2010 09 700·
 2010 08 813.
 2010 07 104.
 2010 06 141.
 2010 05 50·
 2010 04 13·
 2010 03 43.
 2010 02 973.
 2010 01 770.
 2009 12  10·
 2009 11  660·
 2009 10  84·
 2009 09  324.
 2009 08  580·
 2009 07  55.
 2009 06  855.
 2009 05  375·
 2009 02  710·
 2008 10 514.
 2008 09 914·
 2008 08 883.
 2008 07 664·
 2008 06 617·
 2008 05 139·
 2008 04 26·
 2008 03 942.
 2008 02 16
 2008 01 652.
 2007 12  261.
 2007 11  293.
 2007 09  243.
 2007 08  8411·
 2007 07  2711·
 2007 06  727.
 2007 05  17
 2007 04  334.
 2007 03  998.
 2007 02  491.
 2007 01  494·
 2006 12 04.
 2006 11 634·
 2006 10 104.
 2006 06 40.
 2006 05 983.
 2006 04 6110.
 2006 03 303·
 2006 02 885·
 2006 01 653.
 2005 10  642.
 2005 09  102·
 2005 08  335.
 2005 07  646.
 2005 06  640.
 2005 04  755·
 2005 03  959.
 2005 02  836.
 2005 01  8311·
 2004 12 75
 2004 11 566·
 2004 10 349·
 2004 09 626.
 2004 08 864.
 2004 07 226.
 2004 06 552.
 2004 05 735·
 2004 04 97.
 2004 03 256·
 2004 02 1010.
 2004 01 88.
 2003 12  68
 2003 11  2213.
 2003 10  8613.
 2003 09  876·
 2003 08  1410·
 2003 07  956.
 2003 06  978.
 2003 05  553.
 2003 04  231.
 2003 03  491.
 2003 02  793.
 2002 12 797.
 2002 11 947·
 2002 10 189.
 2002 09 967·
 2002 07 562·
 2002 06 544.
 2002 05 564.
 2002 04 365.
 2002 03 27·
 2002 02 52
 2002 01 477.
 2001 12  115.
 2001 11  635.
 2001 10  65
 2001 09  966·
 2001 08  605·
 2001 07  93·
 2001 06  913·
 2001 05  352·
 2001 04  462.
 2001 03  322·
 2001 02  58
 2001 01  22
 2000 12 563·
 2000 11 528.
 2000 10 143.
 2000 09 372·
 2000 08 3
 2000 07 133·
 2000 06 363.
 2000 05 873.
 2000 04 253·
 2000 03 85
 1999 10  253·
 1999 09  47.
 1999 08  853.
 1999 07  617.
 1999 06  42.
 1999 05  440.
 1999 03  723·
 1999 01  612.
 1998 12 256.
 1998 11 905·
 1998 10 977.
 1998 09 296.
 1998 08 645·
 1998 07 477·
 1998 06 983.
 1998 05 342·
 1998 03 193.
 1998 02 483.
 1998 01 403·
 1997 12  695.
 1997 11  187·
 1997 10  495.
 1997 09  8
 1997 08  556·
 1997 07  10
 1997 06  31
 1997 05  186.
 1997 04  365·
 1997 03  713·
 1997 02  26·
 1997 01  56.
 1996 12 807·
 1996 11 04.
 1996 10 924.
 1996 09 332.
 1996 08 813.
 1996 07 255·
 1996 06 604·
 1996 05 916.
 1996 04 60
 1996 03 94
 1996 02 850.
 1996 01 901·
 1995 12  590·
 1995 11  831·
 1995 10  755.
 1995 09  702.
 1995 08  4811.
 1995 07  932·
 1995 06  627·
 1995 05  921.
 1995 04  224.
 1995 03  496.
 1995 02  28.
 1995 01  446·
 1994 12 996.
 1994 11 15.
 1994 10 775.
 1994 09 403·
 1994 08 231.
 1994 07 260.
 1994 06 932.
 1994 04 183.
 1994 03 643·
 1994 02 227·
 1994 01 837.
 1993 12  396.
 1993 11  163·
 1993 10  166.
 1993 09  2
 1993 08  934.
 1993 07  982.
 1993 06  582·
 1993 05  323.
 1993 04  924.
 1993 03  536.
 1993 02  234·
 1993 01  802·
 1992 12 743.
 1992 11 526.
 1992 09 131·
 1992 08 786·
 1992 07 21·
 1992 05 892.
 1992 04 511·
 1992 02 831.
 1992 01 63
 1991 12  813·
 1991 11  891.
 1991 10  753·
 1991 09  71
 1991 08  755·
 1991 07  14·
 1991 06  624·
 1991 05  645.
 1991 03  383·
 1990 12 893.
 1990 11 754.
 1990 10 41.
 1990 09 654.
 1990 08 781·
 1990 07 712.
 1990 06 791.
 1990 05 75
 1990 04 182.
 1990 03 316.
 1990 01 21.
 1989 12  122.
 1989 11  84
 1989 10  632.
 1989 09  127·
 1989 08  463.
 1989 07  782·
 1989 06  972.
 1989 05  701·
 1989 04  709·
 1989 03  237·
 1989 02  904·
 1989 01  662.
 1988 12 44.
 1988 11 718·
 1988 10 251·
 1988 09 111.
 1988 08 911.
 1988 07 982.
 1988 06 73.
 1988 05 438.
 1988 04 13·
 1988 03 28.
 1988 02 697.
 1988 01 26
 1987 12  282.
 1987 10  112.
 1987 09  676.
 1987 08  486·
 1987 07  927.
 1987 06  742·
 1987 05  827.
 1987 04  218·
 1987 03  363.
 1987 02  661.
 1986 10 224·
 1986 09 836.
 1986 08 292·
 1986 07 892·
 1986 06 173.
 1986 05 975.
 1986 04 662.
 1986 03 662·
 1985 12  254·
 1985 11  514.
 1985 10  654·
 1985 09  502.
 1985 08  27
 1985 07  585·
 1985 06  718.
 1985 05  154.
 1985 04  304.
 1985 02  56
 1985 01  542·
 1984 12 619.
 1984 11 654.
 1984 10 7
 1984 09 63.
 1984 08 145.
 1984 07 902·
 1984 06 08.
 1984 05 485·
 1984 04 255·
 1984 03 853.
 1984 02 472·
 1983 12  233.
 1983 11  695.
 1983 10  576·
 1983 09  872.
 1983 08  13.
 1983 07  454.
 1983 06  394.
 1983 05  822.
 1983 04  763.
 1983 03  804·
 1983 02  862.
 1983 01  203.
 1982 12 663·
 1982 11 245.
 1982 10 81
 1982 09 143.
 1982 08 1611.
 1982 07 524.
 1982 06 291·
 1982 05 13·
 1982 04 96
 1982 03 665.
 1982 02 634.
 1982 01 463.
 1981 12  992·
 1981 11  891·
 1981 10  406·
 1981 08  354.
 1981 05  442·
 1981 04  723.
 1981 03  40
 1981 02  824.
 1981 01  76
 1980 12 923·
 1980 11 703.
 1980 10 241.
 1980 09 633.
 1980 08 470·
 1980 07 630·
 1980 06 251·
 1980 04 01·
 1980 03 652·
 1980 02 752.
 1980 01 714.
 1979 12  73.
 1979 11  94
 1979 10  875.
 1979 09  773.
 1979 08  261·
 1979 07  110.
 1979 06  60·
 1979 03  804.
 1979 01  282·
 1978 12 161.
 1978 10 63
 1978 09 432.
 1978 08 67.
 1978 07 347·
 1978 06 173.
 1978 05 543·
 1978 04 791.
 1978 03 152.
 1978 02 472.
 1978 01 252.
 1977 12  921·
 1977 11  353.
 1977 10  602·
 1977 09  954.
 1977 08  141·
 1977 07  954.
 1977 06  89
 1977 05  266·
 1977 04  391.
 1977 03  203.
 1977 02  903.
 1977 01  71.
 1976 12 871·
 1976 10 601.
 1976 09 441.
 1976 08 492·
 1976 07 013.
 1976 06 906.
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US Unemployment Rate: Alternative Measures of Labor Underutilization

Charts

Unemployment Rate: US Unemployment Rate: 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

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      Example 2: Get Employment Data for Workers in the "Retail Trade" Industry







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 Series Title: Employment Level: Nonagriculture, Unpaid Family Workers, 45-54 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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