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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  |  Yearly Chart  |  Excel file  |  Self-updating Excel file
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 1976 06 8395·
 1976 07 80220·
 1976 08 5097.
 1976 09 7061.
 1976 10 4499·
 1976 11 7482.
 1976 12 6780·
 1977 01  5885.
 1977 02  65105.
 1977 03  6154.
 1977 04  7951·
 1977 05  3958.
 1977 06  96101.
 1977 07  21210·
 1977 08  9886·
 1977 09  5643·
 1977 10  13109·
 1977 11  6257·
 1977 12  6362·
 1978 01 7866.
 1978 02 1759.
 1978 03 1572.
 1978 04 3658.
 1978 05 154·
 1978 06 3251.
 1978 07 36191·
 1978 08 669·
 1978 09 4251.
 1978 10 9102.
 1978 11 866·
 1978 12 84100·
 1979 01  4676.
 1979 02  23106.
 1979 03  3863·
 1979 04  1060.
 1979 05  8358.
 1979 06  7572.
 1979 07  55172.
 1979 08  4563·
 1979 09  4670·
 1979 10  91100.
 1979 11  1982·
 1979 12  7977·
 1980 01 5589·
 1980 02 2085·
 1980 03 949.
 1980 04 2265·
 1980 05 5449·
 1980 06 38101.
 1980 07 33251.
 1980 08 1572.
 1980 09 1163·
 1980 10 46115·
 1980 11 2295·
 1980 12 1972.
 1981 01  2163·
 1981 02  6889.
 1981 03  3381.
 1981 04  2271.
 1981 05  389.
 1981 06  55111.
 1981 07  47164.
 1981 08  3875.
 1981 09  264·
 1981 10  8494·
 1981 11  7282.
 1981 12  372.
 1982 01 8690.
 1982 02 52103.
 1982 03 3986.
 1982 04 8268.
 1982 05 4982·
 1982 06 88111.
 1982 07 4236.
 1982 08 6191.
 1982 09 1188·
 1982 10 4089.
 1982 11 4975.
 1982 12 5580.
 1983 01  1689.
 1983 02  8499·
 1983 03  8170·
 1983 04  076·
 1983 05  3357.
 1983 06  2196·
 1983 07  31224·
 1983 08  60103·
 1983 09  5680.
 1983 10  75114·
 1983 11  5681.
 1983 12  2272.
 1984 01 489·
 1984 02 9876.
 1984 03 3862·
 1984 04 9959·
 1984 05 2154.
 1984 06 6575.
 1984 07 84197·
 1984 08 3077·
 1984 09 7770·
 1984 10 75113·
 1984 11 2467.
 1984 12 7774.
 1985 01  6665.
 1985 02  5573.
 1985 03  1644·
 1985 04  2882·
 1985 05  682.
 1985 06  5585·
 1985 07  41174.
 1985 08  9581.
 1985 09  4346.
 1985 10  50100.
 1985 11  653.
 1985 12  1861·
 1986 01 4474·
 1986 02 4176.
 1986 03 4281.
 1986 04 5860·
 1986 05 563·
 1986 06 5390.
 1986 07 7154·
 1986 08 459.
 1986 09 4463·
 1986 10 3676·
 1986 11 8159.
 1986 12 6955.
 1987 01  543.
 1987 02  6685.
 1987 03  7283·
 1987 04  9057.
 1987 05  5958·
 1987 06  4468·
 1987 07  11142.
 1987 08  3068·
 1987 09  9743·
 1987 10  9495·
 1987 11  5567.
 1987 12  7781·
 1988 01 4158.
 1988 02 6652·
 1988 03 8539.
 1988 04 4452.
 1988 05 3458·
 1988 06 3859·
 1988 07 8139·
 1988 08 6946·
 1988 09 4540.
 1988 10 880.
 1988 11 5655.
 1988 12 1540.
 1989 01  6965.
 1989 02  287·
 1989 03  8427.
 1989 04  7032·
 1989 05  2336.
 1989 06  7068.
 1989 07  76131.
 1989 08  4780·
 1989 09  5452.
 1989 10  8968.
 1989 11  3875·
 1989 12  8348.
 1990 01 2985.
 1990 02 5860.
 1990 03 059.
 1990 04 4150·
 1990 05 4352·
 1990 06 349.
 1990 07 21126.
 1990 08 943.
 1990 09 1636·
 1990 10 73104·
 1990 11 8143·
 1990 12 170·
 1991 01  9064.
 1991 02  46103.
 1991 03  8763.
 1991 04  5446·
 1991 05  3667·
 1991 06  2090.
 1991 07  71152.
 1991 08  3156.
 1991 09  4763·
 1991 10  2178·
 1991 11  8979·
 1991 12  1958.
 1992 01 4268.
 1992 02 091·
 1992 03 2365·
 1992 04 3337.
 1992 05 6763·
 1992 06 3277.
 1992 07 80147.
 1992 08 963.
 1992 09 8952·
 1992 10 1879.
 1992 11 9160.
 1992 12 1061.
 1993 01  473·
 1993 02  8276·
 1993 03  1457·
 1993 04  2559·
 1993 05  2966.
 1993 06  7686.
 1993 07  29135.
 1993 08  6686·
 1993 09  1046·
 1993 10  74107·
 1993 11  4355.
 1993 12  7270.
 1994 01 1538.
 1994 02 7762·
 1994 03 8842·
 1994 04 435·
 1994 05 3974·
 1994 06 1177.
 1994 07 2073.
 1994 08 5282.
 1994 09 117.
 1994 10 2662.
 1994 11 2255·
 1994 12 2779.
 1995 01  4453.
 1995 02  9656.
 1995 03  9947·
 1995 04  6818·
 1995 05  3978·
 1995 06  2367.
 1995 07  84124.
 1995 08  3871.
 1995 09  7945.
 1995 10  3365.
 1995 11  3466·
 1995 12  2463·
 1996 01 8243·
 1996 02 7489.
 1996 03 2837·
 1996 04 4044·
 1996 05 9560·
 1996 06 2380·
 1996 07 76103.
 1996 08 2351·
 1996 09 8521·
 1996 10 8187.
 1996 11 770.
 1996 12 3663·
 1997 01  4634.
 1997 02  7266.
 1997 03  7951.
 1997 04  6737.
 1997 05  9939.
 1997 06  4783·
 1997 07  73115.
 1997 08  3088·
 1997 09  8617.
 1997 10  8152·
 1997 11  9641·
 1997 12  6146.
 1998 01 7820.
 1998 02 75104·
 1998 03 7960.
 1998 04 2434·
 1998 05 6840.
 1998 06 5469·
 1998 07 80109·
 1998 08 644·
 1998 09 7531.
 1998 10 6872·
 1998 11 80104·
 1998 12 2130·
 1999 01  4437·
 1999 02  9358.
 1999 03  8538.
 1999 04  745·
 1999 05  4362·
 1999 06  3049·
 1999 07  28130.
 1999 08  2640.
 1999 09  6834·
 1999 10  372.
 1999 11  6464·
 1999 12  6671·
 2000 01 3633.
 2000 02 6376.
 2000 03 7541·
 2000 04 4031.
 2000 05 9337.
 2000 06 8665·
 2000 07 6998·
 2000 08 8662·
 2000 09 619·
 2000 10 7239.
 2000 11 7629.
 2000 12 6865.
 2001 01  7144.
 2001 02  4566·
 2001 03  5451.
 2001 04  7241.
 2001 05  723·
 2001 06  5849.
 2001 07  8498·
 2001 08  1158·
 2001 09  5755.
 2001 10  8462.
 2001 11  7238.


 2001 12  2449·
 2002 01 9225.
 2002 02 2569.
 2002 03 5136·
 2002 04 7453·
 2002 05 436·
 2002 06 582.
 2002 07 76127·
 2002 08 4860·
 2002 09 1339.
 2002 10 7634·
 2002 11 3040·
 2002 12 5945.
 2003 01  6313.
 2003 02  1268.

Similar Series

Skip to Data / More Chart Options

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: 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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