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 Series Title: Employment Level: Pvt W/S Workers, Manufacturing Industry, White, Age 16-24: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Yearly Chart  |  Excel file  |  Self-updating Excel file
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 2003 01  691223·
 2003 02  801234·
 2003 03  141097.
 2003 04  811042.
 2003 05  141050·
 2003 06  481162·
 2003 07  201119·
 2003 08  961231·
 2003 09  261024.
 2003 10  141092·
 2003 11  261165.
 2003 12  101147.
 2004 01 551184.
 2004 02 611054.
 2004 03 461013·
 2004 04 661056.
 2004 05 761100.
 2004 06 951201·
 2004 07 171257·
 2004 08 351318.
 2004 09 891168.
 2004 10 461045.
 2004 11 31020·
 2004 12 91011.
 2005 01  20992.
 2005 02  73955·
 2005 03  92971·
 2005 04  91005.
 2005 05  191028·
 2005 06  571138·
 2005 07  961166·
 2005 08  781041·
 2005 09  621012·
 2005 10  41037.
 2005 11  531119.
 2005 12  861125.
 2006 01 501087.
 2006 02 461045.
 2006 03 271010.
 2006 04 261022.
 2006 05 61068·
 2006 06 391138·
 2006 07 41173.
 2006 08 181241.
 2006 09 831101.
 2006 10 661102·
 2006 11 991063.
 2006 12 61136·
 2007 01  541095.
 2007 02  321074.
 2007 03  481041.
 2007 04  59894.
 2007 05  22993·
 2007 06  701045.
 2007 07  151145.
 2007 08  711101.
 2007 09  101084.
 2007 10  361062.
 2007 11  871101.
 2007 12  621075.
 2008 01 70982·
 2008 02 121028.
 2008 03 78942·
 2008 04 751015.
 2008 05 771045·
 2008 06 51116·
 2008 07 261171.
 2008 08 791125·
 2008 09 31936.
 2008 10 45949.
 2008 11 92918.
 2008 12 70870·
 2009 01  57851·
 2009 02  90861·
 2009 03  66805·
 2009 04  65756·
 2009 05  6747·
 2009 06  22860.
 2009 07  60882.
 2009 08  10827.
 2009 09  54856·
 2009 10  47749·
 2009 11  12774·
 2009 12  72704.
 2010 01 1712·
 2010 02 96721.
 2010 03 84727.
 2010 04 47735.
 2010 05 71721.
 2010 06 26790.
 2010 07 66849.
 2010 08 54808.
 2010 09 17776.
 2010 10 20785·
 2010 11 69798·
 2010 12 36827·
 2011 01  12907·
 2011 02  83911.
 2011 03  31866·
 2011 04  63862·
 2011 05  57802·
 2011 06  47894.
 2011 07  16896.
 2011 08  28934.
 2011 09  78888·
 2011 10  69850·
 2011 11  11901.
 2011 12  52903.
 2012 01 26911·
 2012 02 30912.
 2012 03 29899·
 2012 04 78915.
 2012 05 75860.
 2012 06 38986·
 2012 07 91047·
 2012 08 75963·
 2012 09 251009.
 2012 10 23959·
 2012 11 12947·
 2012 12 38952·
 2013 01  3866·
 2013 02  43880.
 2013 03  27901.
 2013 04  85818.
 2013 05  59887·
 2013 06  79985.
 2013 07  671033·
 2013 08  61991.
 2013 09  67959·
 2013 10  38946·
 2013 11  701013·
 2013 12  351024·
 2014 01 301000·
 2014 02 51967·
 2014 03 98996.
 2014 04 1999.
 2014 05 711011·
 2014 06 741041.
 2014 07 391094.
 2014 08 781104.
 2014 09 411036·
 2014 10 911063.
 2014 11 7901·
 2014 12 11989.
 2015 01  16996.
 2015 02  61002·
 2015 03  39969·
 2015 04  67898·
 2015 05  95929.
 2015 06  531044·
 2015 07  981133·
 2015 08  431064.
 2015 09  6982.
 2015 10  87972.
 2015 11  721009·
 2015 12  561030.
 2016 01 97955·
 2016 02 90972.
 2016 03 741064·
 2016 04 511018.
 2016 05 44989.
 2016 06 701114·
 2016 07 421092.
 2016 08 971110·
 2016 09 48925.
 2016 10 56904.
 2016 11 38913·
 2016 12 88980.
 2017 01  33913.
 2017 02  7993.
 2017 03  511056·
 2017 04  441100.


 2017 05  521046.
 2017 06  31083·
 2017 07  931062.
 2017 08  8946.
 2017 09  77918·
 2017 10  52956·
 2017 11  3899·
 2017 12  49928.
 2018 01 11988·
 2018 02 851001·
 2018 03 421046.
 2018 04 621042.
 2018 05 791099·
 2018 06 581156.
 2018 07 01124.
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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: Employment Level: Pvt W/S Workers, Manufacturing Industry, White, Age 16-24: 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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