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 Series Title: Employment Level: Pvt W/S Workers, Retail trade Industry, Asian, 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  28127.
 2003 02  8197.
 2003 03  3795·
 2003 04  16116·
 2003 05  66123.
 2003 06  32151.
 2003 07  66171·
 2003 08  46170·
 2003 09  33144·
 2003 10  44145·
 2003 11  58156.
 2003 12  36167·
 2004 01 79161.
 2004 02 99103.
 2004 03 27110.
 2004 04 32115.
 2004 05 79140.
 2004 06 3159.
 2004 07 9153·
 2004 08 2151·
 2004 09 35129.
 2004 10 88128.
 2004 11 69134.
 2004 12 41124.
 2005 01  71122·
 2005 02  10117·
 2005 03  94136·
 2005 04  67135.
 2005 05  3899·
 2005 06  52128.
 2005 07  97138.
 2005 08  25134.
 2005 09  11114.
 2005 10  19124·
 2005 11  15125·
 2005 12  85135·
 2006 01 90106.
 2006 02 44101·
 2006 03 12127·
 2006 04 39110·
 2006 05 2102.
 2006 06 83127·
 2006 07 76156.
 2006 08 8167.
 2006 09 96134·
 2006 10 18134·
 2006 11 19112.
 2006 12 35104.
 2007 01  4788.
 2007 02  5594·
 2007 03  79112.
 2007 04  90143.
 2007 05  57136·
 2007 06  26126.
 2007 07  20132.
 2007 08  66108.
 2007 09  50115.
 2007 10  87139·
 2007 11  28162.
 2007 12  84165·
 2008 01 77145·
 2008 02 21121·
 2008 03 18106.
 2008 04 8694.
 2008 05 1495.
 2008 06 34112.
 2008 07 26148.
 2008 08 43152.
 2008 09 60160·
 2008 10 58141·
 2008 11 17109.
 2008 12 47118·
 2009 01  4185·
 2009 02  48103.
 2009 03  7682.
 2009 04  19106·
 2009 05  8130.
 2009 06  88125.
 2009 07  19172.
 2009 08  3134·
 2009 09  3694·
 2009 10  8388.
 2009 11  8293·
 2009 12  6776·
 2010 01 2591·
 2010 02 65113.
 2010 03 28108·
 2010 04 7133·
 2010 05 0117.
 2010 06 91102·
 2010 07 46126·
 2010 08 40126.
 2010 09 13116·
 2010 10 43113.
 2010 11 47111.
 2010 12 11114.
 2011 01  38103.
 2011 02  26144.
 2011 03  71145.
 2011 04  90119·
 2011 05  76107·
 2011 06  73120·
 2011 07  79153·
 2011 08  70128·
 2011 09  52122·
 2011 10  41118.
 2011 11  61111·
 2011 12  7078.
 2012 01 17125·
 2012 02 11126.
 2012 03 28100.
 2012 04 35113.
 2012 05 45106·
 2012 06 89142.
 2012 07 18136·
 2012 08 34153·
 2012 09 38165.
 2012 10 7164·
 2012 11 95153.
 2012 12 61145·
 2013 01  21124.
 2013 02  22116·
 2013 03  46111·
 2013 04  35132.
 2013 05  44133.
 2013 06  16176·
 2013 07  85155·
 2013 08  1148·
 2013 09  83103·
 2013 10  9597.
 2013 11  49101·
 2013 12  26140.
 2014 01 37104·
 2014 02 91130.
 2014 03 0134.
 2014 04 7130·
 2014 05 33175.
 2014 06 60199·
 2014 07 28175·
 2014 08 61167·
 2014 09 21122·
 2014 10 85131.
 2014 11 44137.
 2014 12 32151·
 2015 01  76144.
 2015 02  71128·
 2015 03  87163.
 2015 04  91125.
 2015 05  98140.
 2015 06  51165·
 2015 07  20206·
 2015 08  31186·
 2015 09  13160.
 2015 10  80140·
 2015 11  30153·
 2015 12  70147.
 2016 01 71111.
 2016 02 42100·
 2016 03 31132·
 2016 04 55149.
 2016 05 48143.
 2016 06 41197.
 2016 07 59173.
 2016 08 53152.
 2016 09 45183.
 2016 10 11145·
 2016 11 79156·
 2016 12 58192.
 2017 01  85163.
 2017 02  7153·
 2017 03  78127·
 2017 04  90144.


 2017 05  21143·
 2017 06  11155.
 2017 07  69190.
 2017 08  93192·
 2017 09  26204·
 2017 10  31193·
 2017 11  90188·
 2017 12  37189·
 2018 01 3205.
 2018 02 96197.
 2018 03 3177.
 2018 04 14192.
 2018 05 75177·
 2018 06 65155·
 2018 07 97164.
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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, Retail trade Industry, Asian, 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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