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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  8318·
 2003 02  2618.
 2003 03  2912.
 2003 04  8010·
 2003 05  931·
 2003 06  8612.
 2003 07  7715.
 2003 08  1511·
 2003 09  2712·
 2003 10  11·
 2003 11  8321·
 2003 12  423.
 2004 01 3329.
 2004 02 5215·
 2004 03 590·
 2004 04 9317.
 2004 05 884.
 2004 06 4613·
 2004 07 4313·
 2004 08 5119·
 2004 09 9215.
 2004 10 1513.
 2004 11 9813·
 2004 12 70
 2005 01  694.
 2005 02  1511·
 2005 03  1110.
 2005 04  716·
 2005 05  7218.
 2005 06  2821·
 2005 07  9619.
 2005 08  9818.
 2005 09  7413·
 2005 10  6118.
 2005 11  9015·
 2005 12  1913·
 2006 01 762·
 2006 02 443.
 2006 03 57
 2006 04 297·
 2006 05 56·
 2006 06 369.
 2006 07 853·
 2006 08 4710.
 2006 09 912·
 2006 10 177·
 2006 11 856.
 2006 12 1813.
 2007 01  6510.
 2007 02  9417·
 2007 03  9620.
 2007 04  1013·
 2007 05  7216·
 2007 06  9916·
 2007 07  820.
 2007 08  17
 2007 09  574.
 2007 10  884·
 2007 11  2924·
 2007 12  5915·
 2008 01 7011·
 2008 02 449.
 2008 03 515.
 2008 04 794.
 2008 05 864·
 2008 06 7213·
 2008 07 857.
 2008 08 486.
 2008 09 54.
 2008 10 42·
 2008 11 956.
 2008 12 587·
 2009 01  5314.
 2009 02  989.
 2009 03  69
 2009 04  300·
 2009 05  808·
 2009 06  348·
 2009 07  195·
 2009 08  77.
 2009 09  623.
 2009 10  1910·
 2009 11  834.
 2009 12  58
 2010 01 998·
 2010 02 854·
 2010 03 244.
 2010 04 783.
 2010 05 164.
 2010 06 887.
 2010 07 307.
 2010 08 868·
 2010 09 644·
 2010 10 116.
 2010 11 149·
 2010 12 266.
 2011 01  1917·
 2011 02  605.
 2011 03  135·
 2011 04  664.
 2011 05  794.
 2011 06  669·
 2011 07  9214·
 2011 08  214.
 2011 09  7213.
 2011 10  8613·
 2011 11  377.
 2011 12  520.
 2012 01 470.
 2012 02 2
 2012 03 610.
 2012 04 600·
 2012 05 800.
 2012 06 20
 2012 07 35.
 2012 08 9610·
 2012 09 710·
 2012 10 732.
 2012 11 241·
 2012 12 540.
 2013 01  46
 2013 02  161.
 2013 03  14
 2013 04  534.
 2013 05  541.
 2013 06  314·
 2013 07  859·
 2013 08  361.
 2013 09  726·
 2013 10  2513·
 2013 11  7518·
 2013 12  7413.
 2014 01 9913·
 2014 02 308.
 2014 03 464·
 2014 04 608·
 2014 05 627·
 2014 06 215·
 2014 07 8820·
 2014 08 137·
 2014 09 109·
 2014 10 237·
 2014 11 1113·
 2014 12 788·
 2015 01  192.
 2015 02  996·
 2015 03  555·
 2015 04  2412.
 2015 05  8921·
 2015 06  6216·
 2015 07  8312.
 2015 08  4422.
 2015 09  466.
 2015 10  707·
 2015 11  8211·
 2015 12  592.
 2016 01 4014·
 2016 02 222·
 2016 03 6419.
 2016 04 1119.
 2016 05 468.
 2016 06 679.
 2016 07 694.
 2016 08 716.
 2016 09 6517·
 2016 10 9516·
 2016 11 5917·
 2016 12 3216.
 2017 01  2214·
 2017 02  4416.
 2017 03  2219·
 2017 04  1418·
 2017 05  685·
 2017 06  956.
 2017 07  7015.
 2017 08  6015.
 2017 09  78


 2017 10  5414.
 2017 11  427.
 2017 12  418.
 2018 01 538.
 2018 02 5418·
 2018 03 08·
 2018 04 496·
 2018 05 1711·
 2018 06 5119.
 2018 07 3213.
 2018 08 44.
 2018 09 21
 2018 10 2616.
 2018 11 5218.
 2018 12 5118·
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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
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