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 Series Title: Employed: Retail trade, Asian: NSA
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 2000 01 70741.
 2000 02 49697.
 2000 03 7638·
 2000 04 59646.
 2000 05 44667·
 2000 06 3682.
 2000 07 81755.
 2000 08 50765.
 2000 09 65669.
 2000 10 37638·
 2000 11 37641.
 2000 12 22695.
 2001 01  85704·
 2001 02  33720·
 2001 03  89648·
 2001 04  18631·
 2001 05  77689.
 2001 06  96659·
 2001 07  73738·
 2001 08  6713.
 2001 09  44720·
 2001 10  59728·
 2001 11  53719·
 2001 12  83686.
 2002 01 9669.
 2002 02 78677.
 2002 03 17608·
 2002 04 65681·
 2002 05 25589.
 2002 06 35648·
 2002 07 77755·
 2002 08 98761·
 2002 09 65720.
 2002 10 37763.
 2002 11 72721·
 2002 12 51720.
 2003 01  30635.
 2003 02  14603.
 2003 03  64570.
 2003 04  18636.
 2003 05  46685·
 2003 06  25716·
 2003 07  42786.
 2003 08  18757.
 2003 09  63726.
 2003 10  50657.
 2003 11  18703·
 2003 12  95797·
 2004 01 57752·
 2004 02 97678.
 2004 03 29664.
 2004 04 19607.
 2004 05 28659·
 2004 06 96714.
 2004 07 40736·
 2004 08 83764.
 2004 09 1656·
 2004 10 4658.
 2004 11 38667.
 2004 12 6703·
 2005 01  26737·
 2005 02  4769·
 2005 03  35865.
 2005 04  33771.
 2005 05  80743·
 2005 06  1728·
 2005 07  70751·
 2005 08  33731.
 2005 09  62656.
 2005 10  27657·
 2005 11  6654·
 2005 12  0625.
 2006 01 98679.
 2006 02 40725.
 2006 03 29744·
 2006 04 54692.
 2006 05 38685·
 2006 06 20661·
 2006 07 55686.
 2006 08 37732·
 2006 09 58712.
 2006 10 74702·
 2006 11 19700·
 2006 12 20736·
 2007 01  57697.
 2007 02  35769.
 2007 03  86730.
 2007 04  97737.
 2007 05  62702·
 2007 06  57686.
 2007 07  42660.
 2007 08  86675·
 2007 09  23703.
 2007 10  24769.
 2007 11  1835·
 2007 12  33821.
 2008 01 16801·
 2008 02 42708·
 2008 03 1668.
 2008 04 5688.
 2008 05 39613.
 2008 06 42631·
 2008 07 5670·
 2008 08 97710.
 2008 09 20783.
 2008 10 82809.
 2008 11 0834·
 2008 12 29820.
 2009 01  8739·
 2009 02  42781·
 2009 03  0725.
 2009 04  44762·
 2009 05  79803.
 2009 06  29797.
 2009 07  42834.
 2009 08  12778·
 2009 09  33779.
 2009 10  76790.
 2009 11  89752.
 2009 12  26720.
 2010 01 95668·
 2010 02 38686.
 2010 03 29652.
 2010 04 6716·
 2010 05 16670.
 2010 06 97668·
 2010 07 76778.
 2010 08 96770.
 2010 09 72776.
 2010 10 60799.
 2010 11 66803·
 2010 12 66759.
 2011 01  62652.
 2011 02  59699·
 2011 03  63657.
 2011 04  8684·
 2011 05  13743·
 2011 06  50788·
 2011 07  54757·
 2011 08  43725.
 2011 09  74711.
 2011 10  15740.
 2011 11  53752.
 2011 12  15731·
 2012 01 21809·
 2012 02 61829·
 2012 03 98798.
 2012 04 92758.
 2012 05 54781·
 2012 06 18853·
 2012 07 51827·
 2012 08 69839.
 2012 09 98891·
 2012 10 45838·
 2012 11 0814·
 2012 12 65918·
 2013 01  5830.
 2013 02  22879·
 2013 03  58813·
 2013 04  25804·
 2013 05  49860.
 2013 06  56916·
 2013 07  63866·
 2013 08  16883.
 2013 09  31859·
 2013 10  78815.
 2013 11  79856.
 2013 12  34991.
 2014 01 76925·
 2014 02 461029.
 2014 03 911019·
 2014 04 97919.
 2014 05 35946·
 2014 06 41939·
 2014 07 15951.
 2014 08 50966.
 2014 09 83863.
 2014 10 69837·
 2014 11 87846·
 2014 12 62921.
 2015 01  20929·
 2015 02  631034·
 2015 03  711066·
 2015 04  271001·
 2015 05  72998·
 2015 06  791019·
 2015 07  541028.
 2015 08  64995·
 2015 09  89923·
 2015 10  98804.
 2015 11  49842·
 2015 12  17879.
 2016 01 47859·
 2016 02 28964.
 2016 03 941059·
 2016 04 561072.
 2016 05 46946.
 2016 06 991000·
 2016 07 531010.
 2016 08 74857.
 2016 09 11934·
 2016 10 69953.
 2016 11 12963.
 2016 12 911064.
 2017 01  93988·
 2017 02  18934.
 2017 03  85995·
 2017 04  50977.


 2017 05  661006·
 2017 06  551043·
 2017 07  10928.
 2017 08  22992·
 2017 09  33988.
 2017 10  101015·
 2017 11  49987·
 2017 12  99986·
 2018 01 17989.
 2018 02 40905.
 2018 03 91897.
 2018 04 2925.
 2018 05 70951·
 2018 06 27978·
 2018 07 48952.
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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: 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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