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 Series Title: Employment Level: Nonagriculture, Private Industries Wage and Salary Workers, 16-17 years, Women: NSA
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 2012 04 71615.
 2012 03 52590.
 2012 02 42578·
 2012 01 26602·
 2011 12  12631.
 2011 11  9737·
 2011 10  30777·
 2011 09  17707.
 2011 08  93750·
 2011 07  39760·
 2011 06  94695·
 2011 05  82571.
 2011 04  67567.
 2011 03  24516.
 2011 02  46549·
 2011 01  65565·
 2010 12 8684·
 2010 11 72698.
 2010 10 25739.
 2010 09 34691.
 2010 08 16748·
 2010 07 12712.
 2010 06 94740.
 2010 05 85670.
 2010 04 17662·
 2010 03 3605·
 2010 02 40686·
 2010 01 36690·
 2009 12  61725·
 2009 11  25694·
 2009 10  76699·
 2009 09  31759.
 2009 08  24865·
 2009 07  85926·
 2009 06  41894.
 2009 05  40831·
 2009 04  6777·
 2009 03  16813.
 2009 02  97900·
 2009 01  56799·
 2008 12 33897.
 2008 11 73949·
 2008 10 32997.
 2008 09 991008.
 2008 08 541049·
 2008 07 381078·
 2008 06 581002.
 2008 05 13927.
 2008 04 46990.
 2008 03 18966·
 2008 02 15988.
 2008 01 681013.
 2007 12  81114·
 2007 11  451150.
 2007 10  641122.
 2007 09  561107.
 2007 08  671232·
 2007 07  751279.
 2007 06  941182·
 2007 05  981065·
 2007 04  71999.
 2007 03  90999.
 2007 02  181031.
 2007 01  371055.
 2006 12 981240.
 2006 11 961207·
 2006 10 721275.
 2006 09 431195·
 2006 08 471240.
 2006 07 251350.
 2006 06 211253.
 2006 05 91119.
 2006 04 431112·
 2006 03 341041·
 2006 02 531163.
 2006 01 561095·
 2005 12  371190·
 2005 11  41138.
 2005 10  791148.
 2005 09  271166.
 2005 08  51280·
 2005 07  421372.
 2005 06  381261.
 2005 05  901045·
 2005 04  46980.
 2005 03  801047.
 2005 02  931073·
 2005 01  421080.
 2004 12 871110.
 2004 11 741035.
 2004 10 321041·
 2004 09 991044·
 2004 08 771134.
 2004 07 61266·
 2004 06 671115·
 2004 05 71024·
 2004 04 921030·
 2004 03 831002·
 2004 02 371067.
 2004 01 351086·
 2003 12  331042·
 2003 11  361115.
 2003 10  51059.
 2003 09  771135·
 2003 08  241245·
 2003 07  221320·
 2003 06  571218.
 2003 05  521100.
 2003 04  161080·
 2003 03  221045.
 2003 02  81014·
 2003 01  41067·
 2002 12 851079.
 2002 11 431067·
 2002 10 951125·
 2002 09 31139·
 2002 08 301240·
 2002 07 171303·
 2002 06 801201·
 2002 05 42973·
 2002 04 781012·
 2002 03 11095.
 2002 02 531075.
 2002 01 401037.
 2001 12  791139.
 2001 11  751202.
 2001 10  251189.
 2001 09  421165·
 2001 08  71260.
 2001 07  471396.
 2001 06  351324.
 2001 05  171181.
 2001 04  641116·
 2001 03  491101·
 2001 02  461143·
 2001 01  591182.
 2000 12 751385·
 2000 11 361310.
 2000 10 451234·
 2000 09 881256·
 2000 08 911417·
 2000 07 921475.
 2000 06 451400·
 2000 05 461136.
 2000 04 851191·
 2000 03 211127.
 2000 02 841107.
 2000 01 41193·
 1999 12  601286·
 1999 11  561242·
 1999 10  261253.
 1999 09  561228.
 1999 08  401384·
 1999 07  541533.
 1999 06  571319.
 1999 05  201191·
 1999 04  761209·
 1999 03  961177.
 1999 02  911182·
 1999 01  421157·
 1998 12 431318.
 1998 11 891220.
 1998 10 671237·
 1998 09 891292.
 1998 08 421423·
 1998 07 641506.
 1998 06 451356·
 1998 05 561185.
 1998 04 981176.
 1998 03 781196.
 1998 02 151184·
 1998 01 631181.
 1997 12  611208·
 1997 11  131171.
 1997 10  901147·
 1997 09  531155.
 1997 08  61309·
 1997 07  761409.
 1997 06  71299·
 1997 05  961104.
 1997 04  351129.
 1997 03  971089.
 1997 02  291063.
 1997 01  851119.
 1996 12 731251·
 1996 11 341250.
 1996 10 451242.
 1996 09 401235·
 1996 08 691458·
 1996 07 691503.
 1996 06 661360·
 1996 05 51165·
 1996 04 01123·
 1996 03 71102·
 1996 02 311068.
 1996 01 501092.
 1995 12  651168.
 1995 11  811173.
 1995 10  31143.
 1995 09  671140·
 1995 08  911395·
 1995 07  471366·
 1995 06  691278·
 1995 05  771113·
 1995 04  261020·
 1995 03  871023·
 1995 02  441039.
 1995 01  241055·
 1994 12 481157·
 1994 11 71090.
 1994 10 631096·
 1994 09 761070.
 1994 08 561329·
 1994 07 401323·
 1994 06 911210·
 1994 05 281065.
 1994 04 76973·
 1994 03 41956·
 1994 02 15963·
 1994 01 991001·
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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: Employment Level: Nonagriculture, Private Industries Wage and Salary Workers, 16-17 years, 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

Make charts for Okun's Law and Phillip's Curve

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