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 Series Title: Number Unemployed for 5-6 weeks 16-19 yrs. Male: NSA (Thousands)
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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 2003 02  9668·
 2003 01  1413.
 2002 12 3845.
 2002 11 3940·
 2002 10 1234·
 2002 09 5639·
 2002 08 7060·
 2002 07 84127·
 2002 06 882·
 2002 05 1036·
 2002 04 1753·
 2002 03 4136.
 2002 02 3369.
 2002 01 5625·
 2001 12  8949.
 2001 11  5338.
 2001 10  6262.
 2001 09  155.
 2001 08  2658.
 2001 07  9098·
 2001 06  9749·
 2001 05  7823·
 2001 04  8941·
 2001 03  4551·
 2001 02  6266·
 2001 01  4144.
 2000 12 6865·
 2000 11 3829·
 2000 10 839.
 2000 09 7419·
 2000 08 7562.
 2000 07 1298.
 2000 06 1065·
 2000 05 8337.
 2000 04 4731.
 2000 03 3841·
 2000 02 6876.
 2000 01 9933.
 1999 12  4871.
 1999 11  964·
 1999 10  872·
 1999 09  8034.
 1999 08  6640.
 1999 07  44130·
 1999 06  8149·
 1999 05  662·
 1999 04  1245·
 1999 03  8838.
 1999 02  6258.
 1999 01  8437·
 1998 12 2730.
 1998 11 9104·
 1998 10 5072·
 1998 09 4731.
 1998 08 7144·
 1998 07 2109·
 1998 06 7369.
 1998 05 5040.
 1998 04 3434·
 1998 03 8660.
 1998 02 79104·
 1998 01 7520·
 1997 12  2746.
 1997 11  441.
 1997 10  4452·
 1997 09  2917·
 1997 08  9088.
 1997 07  27115·
 1997 06  6983.
 1997 05  4439·
 1997 04  8437.
 1997 03  4851·
 1997 02  8066.
 1997 01  7734·
 1996 12 9863·
 1996 11 8770.
 1996 10 2587.
 1996 09 821.
 1996 08 4451.
 1996 07 87103.
 1996 06 8280.
 1996 05 4460.
 1996 04 6144·
 1996 03 1837·
 1996 02 5089·
 1996 01 1843·
 1995 12  1163·
 1995 11  7366·
 1995 10  5465·
 1995 09  8545·
 1995 08  8271·
 1995 07  73124·
 1995 06  4667.
 1995 05  2878·
 1995 04  8818·
 1995 03  6147·
 1995 02  056.
 1995 01  5353.
 1994 12 6579.
 1994 11 655.
 1994 10 1662·
 1994 09 9117.
 1994 08 7882.
 1994 07 273.
 1994 06 2177.
 1994 05 074·
 1994 04 1335·
 1994 03 6942·
 1994 02 6562.
 1994 01 6138·
 1993 12  8470·
 1993 11  5155·
 1993 10  22107.
 1993 09  8146·
 1993 08  2886.
 1993 07  16135.
 1993 06  9486.
 1993 05  9166·
 1993 04  959.
 1993 03  5957.
 1993 02  676.
 1993 01  4773.
 1992 12 1461·
 1992 11 060.
 1992 10 879.
 1992 09 3352·
 1992 08 5763·
 1992 07 82147·
 1992 06 7677·
 1992 05 5363.
 1992 04 7437·
 1992 03 7465.
 1992 02 991·
 1992 01 4068.
 1991 12  3058.
 1991 11  7079.
 1991 10  3478·
 1991 09  5163.
 1991 08  1256·
 1991 07  90152.
 1991 06  090·
 1991 05  6767.
 1991 04  3246.
 1991 03  7963·
 1991 02  84103.
 1991 01  9464·
 1990 12 2970.
 1990 11 443.
 1990 10 85104.
 1990 09 6536.
 1990 08 6543·
 1990 07 60126.
 1990 06 2949·
 1990 05 3652·
 1990 04 3050·
 1990 03 6659·
 1990 02 6660·
 1990 01 8985.
 1989 12  3448.
 1989 11  6775·
 1989 10  7268.
 1989 09  3052·
 1989 08  1780.
 1989 07  31131.
 1989 06  4768.
 1989 05  9136.
 1989 04  4032.
 1989 03  5327.
 1989 02  1787.
 1989 01  2965.
 1988 12 9340.
 1988 11 5155·
 1988 10 3180·
 1988 09 2440·
 1988 08 8846·
 1988 07 71139.
 1988 06 6659.
 1988 05 8558.
 1988 04 6352.
 1988 03 8139·
 1988 02 2152.
 1988 01 4258·
 1987 12  8081.
 1987 11  7567.
 1987 10  2395·
 1987 09  5343.
 1987 08  2868.
 1987 07  72142·
 1987 06  2068.
 1987 05  9858.
 1987 04  1957.
 1987 03  1683·
 1987 02  9085·
 1987 01  8443·
 1986 12 9255.
 1986 11 7859.
 1986 10 3176·
 1986 09 4463·
 1986 08 959.
 1986 07 50154·
 1986 06 7190·
 1986 05 3363·
 1986 04 5860·
 1986 03 5281·
 1986 02 5876·
 1986 01 3474·
 1985 12  5261.
 1985 11  2853·
 1985 10  69100.
 1985 09  5346.
 1985 08  3081·
 1985 07  47174.
 1985 06  385·
 1985 05  2182·
 1985 04  5382·
 1985 03  444.
 1985 02  8773·
 1985 01  9665·
 1984 12 974.
 1984 11 1767·
 1984 10 70113.
 1984 09 5870·
 1984 08 1377·
 1984 07 31197.
 1984 06 2875·
 1984 05 1554.
 1984 04 159.
 1984 03 1462·
 1984 02 6176.
 1984 01 9989·
 1983 12  3672.
 1983 11  6181.
 1983 10  95114.
 1983 09  6580·
 1983 08  6103·
 1983 07  92224·
 1983 06  8196.
 1983 05  9657·
 1983 04  2576·
 1983 03  4970.
 1983 02  9299.
 1983 01  9789·
 1982 12 3080.
 1982 11 375.
 1982 10 3189·
 1982 09 288·
 1982 08 8491.
 1982 07 48236·
 1982 06 22111.
 1982 05 6682·
 1982 04 7468·
 1982 03 286·
 1982 02 15103·
 1982 01 7190·
 1981 12  1472.
 1981 11  982·
 1981 10  8794.
 1981 09  2364·
 1981 08  4275·
 1981 07  40164·
 1981 06  37111·
 1981 05  5589·
 1981 04  2171.
 1981 03  8781.
 1981 02  9189.
 1981 01  2363.
 1980 12 3872.
 1980 11 7195·
 1980 10 99115.
 1980 09 963.
 1980 08 672.
 1980 07 35251.
 1980 06 36101.
 1980 05 1949.
 1980 04 6365·
 1980 03 4949·
 1980 02 485·
 1980 01 8589·
 1979 12  7377·
 1979 11  682·
 1979 10  27100·
 1979 09  6370·
 1979 08  2263·
 1979 07  26172.
 1979 06  5672·
 1979 05  3558·
 1979 04  2460.
 1979 03  5263.
 1979 02  66106.
 1979 01  876.
 1978 12 17100.
 1978 11 5566·
 1978 10 58102·
 1978 09 1451·
 1978 08 6469.
 1978 07 28191.
 1978 06 5751·
 1978 05 954.
 1978 04 5258·
 1978 03 9072.
 1978 02 1359.
 1978 01 7466·
 1977 12  9562.
 1977 11  8657.
 1977 10  1109.
 1977 09  1743.
 1977 08  3086·
 1977 07  84210.
 1977 06  23101·
 1977 05  6958·
 1977 04  2051.
 1977 03  7954·
 1977 02  4105·
 1977 01  8785·
 1976 12 5380.
 1976 11 8982.
 1976 10 9399·
 1976 09 5261·
 1976 08 4297·
 1976 07 60220.
 1976 06 6795.
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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 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: Number Unemployed for 5-6 weeks 16-19 yrs. Male: NSA (Thousands)
   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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