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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  70127.
 2003 02  897·
 2003 03  3095.
 2003 04  57116.
 2003 05  35123.
 2003 06  11151.
 2003 07  35171.
 2003 08  88170·
 2003 09  28144.
 2003 10  75145·
 2003 11  4156·
 2003 12  80167.
 2004 01 1161.
 2004 02 81103·
 2004 03 49110·
 2004 04 77115·
 2004 05 28140·
 2004 06 36159·
 2004 07 9153.
 2004 08 49151·
 2004 09 10129.
 2004 10 73128·
 2004 11 45134.
 2004 12 89124.
 2005 01  72122.
 2005 02  47117·
 2005 03  46136.
 2005 04  17135·
 2005 05  6699.
 2005 06  40128.
 2005 07  26138·
 2005 08  77134·
 2005 09  65114·
 2005 10  59124·
 2005 11  21125·
 2005 12  38135.
 2006 01 72106·
 2006 02 35101.
 2006 03 94127·
 2006 04 94110·
 2006 05 10102.
 2006 06 26127.
 2006 07 34156.
 2006 08 64167.
 2006 09 30134·
 2006 10 12134.
 2006 11 54112·
 2006 12 93104.
 2007 01  888.
 2007 02  094·
 2007 03  91112.
 2007 04  49143·
 2007 05  45136.
 2007 06  23126.
 2007 07  8132·
 2007 08  27108.
 2007 09  64115·
 2007 10  36139·
 2007 11  93162·
 2007 12  46165·
 2008 01 18145·
 2008 02 22121.
 2008 03 59106·
 2008 04 5094·
 2008 05 8195·
 2008 06 86112·
 2008 07 44148.
 2008 08 8152.
 2008 09 54160.
 2008 10 61141.
 2008 11 11109·
 2008 12 14118·
 2009 01  6285·
 2009 02  4103·
 2009 03  4882·
 2009 04  88106.
 2009 05  55130.
 2009 06  95125.
 2009 07  67172.
 2009 08  73134·
 2009 09  994·
 2009 10  4188.
 2009 11  693·
 2009 12  3976.
 2010 01 2591.
 2010 02 75113·
 2010 03 29108·
 2010 04 80133.
 2010 05 27117.
 2010 06 53102.
 2010 07 23126·
 2010 08 15126.
 2010 09 66116.
 2010 10 56113·
 2010 11 1111·
 2010 12 87114.
 2011 01  18103·
 2011 02  91144·
 2011 03  1145.
 2011 04  68119.
 2011 05  82107.
 2011 06  90120·
 2011 07  86153.
 2011 08  49128.
 2011 09  85122·
 2011 10  9118.
 2011 11  44111.
 2011 12  5178·
 2012 01 76125·
 2012 02 30126·
 2012 03 88100·
 2012 04 18113·
 2012 05 31106.
 2012 06 59142·
 2012 07 55136·
 2012 08 19153.
 2012 09 51165.
 2012 10 29164·
 2012 11 8153·
 2012 12 47145·
 2013 01  60124·
 2013 02  96116.
 2013 03  36111·
 2013 04  23132·
 2013 05  10133.
 2013 06  42176·
 2013 07  51155·
 2013 08  90148·
 2013 09  75103·
 2013 10  7297·
 2013 11  92101·
 2013 12  17140.
 2014 01 56104.
 2014 02 20130.
 2014 03 20134.
 2014 04 99130.
 2014 05 79175.
 2014 06 41199.
 2014 07 24175·
 2014 08 54167.
 2014 09 93122.
 2014 10 17131·
 2014 11 17137.
 2014 12 27151·
 2015 01  74144.
 2015 02  54128·
 2015 03  37163.
 2015 04  87125·
 2015 05  23140·
 2015 06  86165·
 2015 07  46206·
 2015 08  29186·
 2015 09  65160·
 2015 10  67140·
 2015 11  33153.
 2015 12  70147.
 2016 01 50111·
 2016 02 80100.
 2016 03 10132.
 2016 04 56149·
 2016 05 53143·
 2016 06 31197.
 2016 07 15173·
 2016 08 55152.
 2016 09 76183.
 2016 10 52145·
 2016 11 12156.
 2016 12 62192.
 2017 01  43163·
 2017 02  0153·
 2017 03  87127·
 2017 04  96144·
 2017 05  5143·
 2017 06  56155.


 2017 07  54190·
 2017 08  1192·
 2017 09  37204.
 2017 10  26193·
 2017 11  52188·
 2017 12  46189.
 2018 01 40205.
 2018 02 44197.
 2018 03 42177.
 2018 04 25192·
 2018 05 39177.
 2018 06 64155.
 2018 07 12164.
 2018 08 57119.
 2018 09 85116·
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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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