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 Series Title: Employment Level: Pvt W/S Workers, Wholesale trade Industry, Asian, Age 16-24: NSA
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 2003 01  8518.
 2003 02  7918.
 2003 03  3812.
 2003 04  1910·
 2003 05  71·
 2003 06  8612.
 2003 07  4415.
 2003 08  9711·
 2003 09  4412·
 2003 10  411·
 2003 11  121.
 2003 12  2423·
 2004 01 4929.
 2004 02 2615·
 2004 03 21
 2004 04 4417·
 2004 05 954.
 2004 06 4713.
 2004 07 4413.
 2004 08 2619·
 2004 09 8415·
 2004 10 3813.
 2004 11 3113·
 2004 12 635·
 2005 01  414.
 2005 02  5311·
 2005 03  7010.
 2005 04  766.
 2005 05  1618.
 2005 06  7521.
 2005 07  7519·
 2005 08  918.
 2005 09  8513.
 2005 10  1018·
 2005 11  8315.
 2005 12  2913·
 2006 01 482.
 2006 02 903.
 2006 03 573.
 2006 04 337.
 2006 05 316·
 2006 06 719.
 2006 07 853.
 2006 08 3810.
 2006 09 8312·
 2006 10 367.
 2006 11 816.
 2006 12 8913·
 2007 01  8110·
 2007 02  9117·
 2007 03  8120.
 2007 04  5613.
 2007 05  2416·
 2007 06  6816·
 2007 07  480·
 2007 08  316.
 2007 09  38
 2007 10  224·
 2007 11  7224·
 2007 12  3515.
 2008 01 7311·
 2008 02 369.
 2008 03 635.
 2008 04 114.
 2008 05 64.
 2008 06 1713·
 2008 07 617·
 2008 08 296.
 2008 09 364.
 2008 10 962·
 2008 11 296·
 2008 12 837·
 2009 01  8814.
 2009 02  299.
 2009 03  532.
 2009 04  920.
 2009 05  138·
 2009 06  998·
 2009 07  485.
 2009 08  07.
 2009 09  863·
 2009 10  1210.
 2009 11  514.
 2009 12  755·
 2010 01 98·
 2010 02 994·
 2010 03 244.
 2010 04 143.
 2010 05 54.
 2010 06 187·
 2010 07 567.
 2010 08 338·
 2010 09 264.
 2010 10 50
 2010 11 609.
 2010 12 796.
 2011 01  4717.
 2011 02  15.
 2011 03  73
 2011 04  194.
 2011 05  684·
 2011 06  49.
 2011 07  5914·
 2011 08  4814·
 2011 09  1513.
 2011 10  1413·
 2011 11  57·
 2011 12  850·
 2012 01 380·
 2012 02 140·
 2012 03 240.
 2012 04 74
 2012 05 130.
 2012 06 109.
 2012 07 545.
 2012 08 8510.
 2012 09 400.
 2012 10 332·
 2012 11 581.
 2012 12 110.
 2013 01  431·
 2013 02  411.
 2013 03  241·
 2013 04  714·
 2013 05  751·
 2013 06  164.
 2013 07  659·
 2013 08  101·
 2013 09  96.
 2013 10  6213.
 2013 11  1818·
 2013 12  9813·
 2014 01 4713·
 2014 02 138.
 2014 03 474·
 2014 04 278·
 2014 05 14
 2014 06 2615·
 2014 07 3920.
 2014 08 177·
 2014 09 609.
 2014 10 807.
 2014 11 813.
 2014 12 138.
 2015 01  602.
 2015 02  846.
 2015 03  905·
 2015 04  8312·
 2015 05  1621.
 2015 06  6916.
 2015 07  5012.
 2015 08  2222.
 2015 09  526·
 2015 10  927·
 2015 11  7511·
 2015 12  482.
 2016 01 1914·
 2016 02 3322.
 2016 03 7819.
 2016 04 719.
 2016 05 928.
 2016 06 09·
 2016 07 964·
 2016 08 66
 2016 09 7117.
 2016 10 2516·
 2016 11 9317·
 2016 12 2016.
 2017 01  8314.
 2017 02  6416·
 2017 03  5719.
 2017 04  8918·


 2017 05  775.
 2017 06  996·
 2017 07  015.
 2017 08  1615.
 2017 09  285.
 2017 10  3614·
 2017 11  607.
 2017 12  718.
 2018 01 388·
 2018 02 718.
 2018 03 18.
 2018 04 486.
 2018 05 3211.
 2018 06 6919·
 2018 07 913.
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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, Wholesale 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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