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 Series Title: Employment Level: Multiple Jobholders, Asian Women: 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 98135.
 2000 02 59124.
 2000 03 6133.
 2000 04 80147·
 2000 05 44111.
 2000 06 6797·
 2000 07 15113·
 2000 08 8789·
 2000 09 63114.
 2000 10 79113.
 2000 11 31129.
 2000 12 0124·
 2001 01  5133·
 2001 02  78133.
 2001 03  6795.
 2001 04  61112·
 2001 05  45107.
 2001 06  69111·
 2001 07  61115·
 2001 08  41121.
 2001 09  83115.
 2001 10  86113.
 2001 11  76141.
 2001 12  33121·
 2002 01 46135.
 2002 02 84146.
 2002 03 99119.
 2002 04 57135·
 2002 05 84127.
 2002 06 44122·
 2002 07 44118.
 2002 08 5699·
 2002 09 71104·
 2002 10 74106.
 2002 11 49145.
 2002 12 0131.
 2003 01  9110·
 2003 02  692·
 2003 03  7697.
 2003 04  8396.
 2003 05  22123.
 2003 06  95130.
 2003 07  13107.
 2003 08  2493·
 2003 09  6185.
 2003 10  2474·
 2003 11  7493·
 2003 12  67107·
 2004 01 2110.
 2004 02 98162·
 2004 03 95113·
 2004 04 82143.
 2004 05 45108·
 2004 06 5175.
 2004 07 4180·
 2004 08 6180.
 2004 09 1595·
 2004 10 3893.
 2004 11 98122·
 2004 12 26119.
 2005 01  63125.
 2005 02  41133.
 2005 03  80120.
 2005 04  19139·
 2005 05  64120.
 2005 06  67168·
 2005 07  25117·
 2005 08  10130.
 2005 09  18122·
 2005 10  47143.
 2005 11  95115.
 2005 12  93109·
 2006 01 52107.
 2006 02 38132·
 2006 03 79136.
 2006 04 8898·
 2006 05 14126·
 2006 06 21110·
 2006 07 89108·
 2006 08 37121·
 2006 09 8188.
 2006 10 4136.
 2006 11 63133·
 2006 12 11170·
 2007 01  53160·
 2007 02  18168.
 2007 03  64129·
 2007 04  4141·
 2007 05  55130·
 2007 06  19107.
 2007 07  81118.
 2007 08  34123.
 2007 09  39135.
 2007 10  90122.
 2007 11  25125.
 2007 12  47101·
 2008 01 78116·
 2008 02 36135·
 2008 03 34151·
 2008 04 10161.
 2008 05 74137·
 2008 06 90151.
 2008 07 73154·
 2008 08 18151·
 2008 09 52130.
 2008 10 8109.
 2008 11 28110·
 2008 12 91125·
 2009 01  62102·
 2009 02  71113·
 2009 03  12106.
 2009 04  72121.
 2009 05  80120·
 2009 06  87112·
 2009 07  64100·
 2009 08  31114·
 2009 09  6100·
 2009 10  8766.
 2009 11  4687.
 2009 12  6153·
 2010 01 66103.
 2010 02 2883·
 2010 03 4691·
 2010 04 82126.
 2010 05 10120.
 2010 06 9191.
 2010 07 77121·
 2010 08 39139·
 2010 09 13106·
 2010 10 82110.
 2010 11 77114·
 2010 12 9973·
 2011 01  7594.
 2011 02  35112.
 2011 03  9128·
 2011 04  58118.
 2011 05  23114·
 2011 06  4124·
 2011 07  6093.
 2011 08  3469.
 2011 09  6114·
 2011 10  73111.
 2011 11  44133·
 2011 12  71130.
 2012 01 0133·
 2012 02 47150.
 2012 03 98142.
 2012 04 39142·
 2012 05 6127·
 2012 06 5898·
 2012 07 86125·
 2012 08 33112·
 2012 09 48133·
 2012 10 63128·
 2012 11 95145·
 2012 12 70165.
 2013 01  77165.
 2013 02  43174.
 2013 03  38146·
 2013 04  95119.
 2013 05  68169.
 2013 06  6158·
 2013 07  53156·
 2013 08  77145·
 2013 09  22145.
 2013 10  82111·
 2013 11  3136·
 2013 12  11161·
 2014 01 65142·
 2014 02 28181.
 2014 03 75171.
 2014 04 16129·
 2014 05 46146·
 2014 06 27144·
 2014 07 84134.
 2014 08 35140·
 2014 09 41138.
 2014 10 84155·
 2014 11 66154·
 2014 12 38108.
 2015 01  50132·
 2015 02  31145·
 2015 03  84155.
 2015 04  19169.
 2015 05  0164.
 2015 06  25145.
 2015 07  27130.
 2015 08  96116.
 2015 09  39155.
 2015 10  48153·
 2015 11  7145.
 2015 12  16194.
 2016 01 44118.
 2016 02 6140·
 2016 03 62165.
 2016 04 45155·
 2016 05 15163.
 2016 06 31158·
 2016 07 55215·
 2016 08 79213.
 2016 09 77180.
 2016 10 79151.
 2016 11 74168.
 2016 12 37150·
 2017 01  81144.
 2017 02  32152.
 2017 03  32157·
 2017 04  63192·
 2017 05  2174·
 2017 06  97129·


 2017 07  66130·
 2017 08  25129.
 2017 09  41128.
 2017 10  6140.
 2017 11  40138.
 2017 12  19186·
 2018 01 23137·
 2018 02 14168·
 2018 03 42144·
 2018 04 63112.
 2018 05 97118·
 2018 06 5136.
 2018 07 84154.
 2018 08 1141.
 2018 09 41149.
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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: Multiple Jobholders, Asian Women: 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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