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 Series Title: Employed: Wholesale and retail trade, Asian: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Yearly Chart  |  Excel file  |  Self-updating Excel file
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 2000 01 35901.
 2000 02 29883.
 2000 03 9775·
 2000 04 52809·
 2000 05 61840.
 2000 06 39829.
 2000 07 92904·
 2000 08 56943.
 2000 09 47882.
 2000 10 41856·
 2000 11 69822·
 2000 12 52862.
 2001 01  44884.
 2001 02  17915.
 2001 03  54861.
 2001 04  84864.
 2001 05  27899·
 2001 06  73860.
 2001 07  85892.
 2001 08  22890·
 2001 09  96901·
 2001 10  42898·
 2001 11  24869·
 2001 12  60826·
 2002 01 77789.
 2002 02 79818.
 2002 03 59752·
 2002 04 17843.
 2002 05 19768·
 2002 06 67836.
 2002 07 3970·
 2002 08 38976·
 2002 09 99926·
 2002 10 11965·
 2002 11 94907·
 2002 12 90875.
 2003 01  17793.
 2003 02  45761.
 2003 03  95704.
 2003 04  69773.
 2003 05  98831·
 2003 06  24896.
 2003 07  94987·
 2003 08  93932.
 2003 09  93913.
 2003 10  30797.
 2003 11  3893·
 2003 12  7997·
 2004 01 77940.
 2004 02 69857·
 2004 03 61835·
 2004 04 80810·
 2004 05 50855.
 2004 06 74952.
 2004 07 31945·
 2004 08 6977·
 2004 09 38854.
 2004 10 1851.
 2004 11 0880.
 2004 12 4888·
 2005 01  91925·
 2005 02  31977·
 2005 03  811039.
 2005 04  18936·
 2005 05  85905.
 2005 06  71902.
 2005 07  12914.
 2005 08  17910.
 2005 09  19878.
 2005 10  53881·
 2005 11  57885.
 2005 12  96871.
 2006 01 20887·
 2006 02 34900.
 2006 03 2893·
 2006 04 74857.
 2006 05 38877·
 2006 06 95836.
 2006 07 61874.
 2006 08 94893.
 2006 09 48900.
 2006 10 42906.
 2006 11 71919·
 2006 12 27971.
 2007 01  50895.
 2007 02  8969.
 2007 03  97955·
 2007 04  65951·
 2007 05  70922·
 2007 06  49878.
 2007 07  24823·
 2007 08  29855.
 2007 09  59847·
 2007 10  47942·
 2007 11  681048.
 2007 12  621015.
 2008 01 91988·
 2008 02 8874.
 2008 03 64831·
 2008 04 34884·
 2008 05 67787·
 2008 06 63810.
 2008 07 76854.
 2008 08 38878·
 2008 09 13919.
 2008 10 71975·
 2008 11 931016.
 2008 12 94970.
 2009 01  78889.
 2009 02  12942·
 2009 03  26894·
 2009 04  46925.
 2009 05  39995.
 2009 06  92994·
 2009 07  15978·
 2009 08  63928·
 2009 09  96938.
 2009 10  44935.
 2009 11  21900·
 2009 12  40856.
 2010 01 73805.
 2010 02 25815·
 2010 03 32817.
 2010 04 94907·
 2010 05 22887·
 2010 06 15913·
 2010 07 621028·
 2010 08 711010.
 2010 09 18976.
 2010 10 21942·
 2010 11 49953·
 2010 12 40874.
 2011 01  61789.
 2011 02  76867.
 2011 03  54832.
 2011 04  95893·
 2011 05  76956·
 2011 06  351003.
 2011 07  67933.
 2011 08  54884.
 2011 09  15869·
 2011 10  81900·
 2011 11  0908.
 2011 12  63889.
 2012 01 511004.
 2012 02 191005.
 2012 03 91957·
 2012 04 89909·
 2012 05 87965·
 2012 06 831064·
 2012 07 31023·
 2012 08 281069.
 2012 09 471080.
 2012 10 27989·
 2012 11 23979·
 2012 12 991122·
 2013 01  811042·
 2013 02  351080.
 2013 03  65986·
 2013 04  45967·
 2013 05  651020.
 2013 06  121071.
 2013 07  671062·
 2013 08  361063.
 2013 09  01026·
 2013 10  90962·
 2013 11  911033.
 2013 12  661178·
 2014 01 101104·
 2014 02 261216·
 2014 03 251174.
 2014 04 531076.
 2014 05 461099.
 2014 06 11109.
 2014 07 821148.
 2014 08 431134·
 2014 09 841035.
 2014 10 23987.
 2014 11 11052.
 2014 12 51129·
 2015 01  241116·
 2015 02  231250·
 2015 03  431260·
 2015 04  321237.
 2015 05  911223.
 2015 06  561214.
 2015 07  971200.
 2015 08  431166·
 2015 09  361079.
 2015 10  61007.
 2015 11  761013.
 2015 12  831061·
 2016 01 331067·
 2016 02 791209·
 2016 03 181281.
 2016 04 211278·
 2016 05 851171.
 2016 06 61218·
 2016 07 851234·
 2016 08 511082.
 2016 09 151143.
 2016 10 441189.
 2016 11 651171.
 2016 12 921270·
 2017 01  741224·
 2017 02  741127.
 2017 03  721200·
 2017 04  891206·
 2017 05  381230·
 2017 06  41244.
 2017 07  431196.
 2017 08  101235.


 2017 09  71169·
 2017 10  651208·
 2017 11  411156·
 2017 12  491137.
 2018 01 61119.
 2018 02 131049·
 2018 03 541044·
 2018 04 261113·
 2018 05 861173·
 2018 06 301216·
 2018 07 951173·
 2018 08 851156.
 2018 09 221084·
 2018 10 231110.
 2018 11 21177·
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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: Employed: Wholesale and retail trade, Asian: 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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