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 Series Title: Population Level: 16-19 years, Hispanic or Latino Women: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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 2012 04 21775·
 2012 03 691774·
 2012 02 681774·
 2012 01 321773·
 2011 12  191606.
 2011 11  911605.
 2011 10  81603.
 2011 09  631601·
 2011 08  291598.
 2011 07  361596.
 2011 06  741594.
 2011 05  171592.
 2011 04  791590.
 2011 03  861587.
 2011 02  781585·
 2011 01  401583.
 2010 12 471588.
 2010 11 481586.
 2010 10 601584.
 2010 09 991582·
 2010 08 331580·
 2010 07 531578.
 2010 06 811576·
 2010 05 901575.
 2010 04 611573.
 2010 03 591572·
 2010 02 291570.
 2010 01 301568.
 2009 12  831549·
 2009 11  461546.
 2009 10  181544·
 2009 09  661540·
 2009 08  731536.
 2009 07  211533.
 2009 06  851529.
 2009 05  641526.
 2009 04  331523·
 2009 03  161519·
 2009 02  931515.
 2009 01  201511·
 2008 12 871518.
 2008 11 881512.
 2008 10 301507·
 2008 09 531502.
 2008 08 861496·
 2008 07 191491·
 2008 06 91486·
 2008 05 71481·
 2008 04 51476·
 2008 03 141471·
 2008 02 681466.
 2008 01 511460·
 2007 12  441467·
 2007 11  51462.
 2007 10  701457·
 2007 09  801452.
 2007 08  301446·
 2007 07  501441·
 2007 06  21436.
 2007 05  111431·
 2007 04  121426.
 2007 03  291421·
 2007 02  781416.
 2007 01  901412.
 2006 12 661399.
 2006 11 501393·
 2006 10 351388.
 2006 09 861382.
 2006 08 921377.
 2006 07 441371·
 2006 06 371365·
 2006 05 921360·
 2006 04 161354·
 2006 03 681349·
 2006 02 701343·
 2006 01 291338·
 2005 12  871339·
 2005 11  31333.
 2005 10  491328.
 2005 09  391323.
 2005 08  821319·
 2005 07  561314.
 2005 06  101310.
 2005 05  931306·
 2005 04  11302·
 2005 03  591299·
 2005 02  181295.
 2005 01  841292.
 2004 12 691291.
 2004 11 681287·
 2004 10 591283.
 2004 09 311280.
 2004 08 371277.
 2004 07 651273.
 2004 06 471270·
 2004 05 791267·
 2004 04 791264·
 2004 03 561260·
 2004 02 191257·
 2004 01 971254.
 2003 12  971260.
 2003 11  741257·
 2003 10  391254·
 2003 09  791251.
 2003 08  151247.
 2003 07  751244·
 2003 06  931240.
 2003 05  441236·
 2003 04  851232·
 2003 03  401229.
 2003 02  961227.
 2003 01  361225.
 2002 12 811222·
 2002 11 761221.
 2002 10 861220.
 2002 09 241218·
 2002 08 41216·
 2002 07 151214.
 2002 06 241212.
 2002 05 31210·
 2002 04 791208.
 2002 03 131207·
 2002 02 991207.
 2002 01 911206·
 2001 12  571205.
 2001 11  521204·
 2001 10  231203·
 2001 09  331202·
 2001 08  131201.
 2001 07  391199.
 2001 06  361198.
 2001 05  981196·
 2001 04  471194·
 2001 03  61193.
 2001 02  991192.
 2001 01  801190·
 2000 12 861191·
 2000 11 81190.
 2000 10 01192·
 2000 09 981191·
 2000 08 781191.
 2000 07 281190.
 2000 06 521190.
 2000 05 971190.
 2000 04 01189·
 2000 03 721188·
 2000 02 941188·
 2000 01 441189·
 1999 12  521130·
 1999 11  721128.
 1999 10  881127·
 1999 09  361125.
 1999 08  601122·
 1999 07  851119·
 1999 06  221116.
 1999 05  901113·
 1999 04  731110·
 1999 03  921106·
 1999 02  81103.
 1999 01  511100·
 1998 12 671063.
 1998 11 991060.
 1998 10 861056.
 1998 09 881052·
 1998 08 431048.
 1998 07 391044.
 1998 06 171041.
 1998 05 951038·
 1998 04 271035.
 1998 03 691032·
 1998 02 891029.
 1998 01 921026·
 1997 12  671017.
 1997 11  681014.
 1997 10  161012·
 1997 09  221010·
 1997 08  401007·
 1997 07  461005·
 1997 06  361001·
 1997 05  54999.
 1997 04  46996.
 1997 03  32993.
 1997 02  10990·
 1997 01  84987·
 1996 12 11975·
 1996 11 84972.
 1996 10 28968.
 1996 09 29965·
 1996 08 85961·
 1996 07 83958·
 1996 06 1954·
 1996 05 34951·
 1996 04 43947·
 1996 03 36943·
 1996 02 69940·
 1996 01 68937·
 1995 12  85934.
 1995 11  75931.
 1995 10  93929.
 1995 09  25926.
 1995 08  38923·
 1995 07  56921.
 1995 06  62919.
 1995 05  25917·
 1995 04  51917·
 1995 03  61921·
 1995 02  89870·
 1995 01  12906.
 1994 12 1902.
 1994 11 96900·
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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

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: Population Level: 16-19 years, Hispanic or Latino Women: 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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