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 Series Title: Employment Level: Multiple Jobholders, 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 69247·
 2000 02 49222.
 2000 03 30250·
 2000 04 4288·
 2000 05 85206·
 2000 06 88225·
 2000 07 34244·
 2000 08 69205·
 2000 09 23251.
 2000 10 83225.
 2000 11 94257·
 2000 12 88241·
 2001 01  34246·
 2001 02  14252.
 2001 03  25243·
 2001 04  7276·
 2001 05  94228·
 2001 06  87265.
 2001 07  63227·
 2001 08  94240·
 2001 09  2252·
 2001 10  36241·
 2001 11  73248·
 2001 12  43226·
 2002 01 84235·
 2002 02 16277·
 2002 03 41270.
 2002 04 74269.
 2002 05 91243·
 2002 06 8248·
 2002 07 80234·
 2002 08 30206·
 2002 09 98222.
 2002 10 20205·
 2002 11 29260·
 2002 12 81236.
 2003 01  5187.
 2003 02  84198·
 2003 03  51199.
 2003 04  21195·
 2003 05  38240·
 2003 06  55217·
 2003 07  33202·
 2003 08  69196.
 2003 09  47190.
 2003 10  16154·
 2003 11  88170·
 2003 12  69206·
 2004 01 8192·
 2004 02 73276.
 2004 03 54231.
 2004 04 91248.
 2004 05 20221.
 2004 06 57194.
 2004 07 94215·
 2004 08 27194·
 2004 09 10198·
 2004 10 26191·
 2004 11 96278·
 2004 12 99274·
 2005 01  27257.
 2005 02  61281.
 2005 03  73226·
 2005 04  49223·
 2005 05  48213.
 2005 06  69277.
 2005 07  62239.
 2005 08  47264.
 2005 09  71251.
 2005 10  81320·
 2005 11  27269·
 2005 12  88261.
 2006 01 24262·
 2006 02 54282.
 2006 03 55253·
 2006 04 89233·
 2006 05 56239.
 2006 06 70243.
 2006 07 59242.
 2006 08 96243.
 2006 09 43203.
 2006 10 35250.
 2006 11 78239.
 2006 12 77295.
 2007 01  84276.
 2007 02  81312·
 2007 03  74284·
 2007 04  26247.
 2007 05  6254·
 2007 06  64216.
 2007 07  35253.
 2007 08  64239·
 2007 09  59237.
 2007 10  66220·
 2007 11  73220.
 2007 12  33235·
 2008 01 18218.
 2008 02 95266·
 2008 03 28283·
 2008 04 3306·
 2008 05 83263·
 2008 06 80266·
 2008 07 61262.
 2008 08 69287.
 2008 09 81248·
 2008 10 80213.
 2008 11 60200.
 2008 12 48234·
 2009 01  60213.
 2009 02  76210.
 2009 03  39212·
 2009 04  86248·
 2009 05  98262·
 2009 06  74236.
 2009 07  35183.
 2009 08  52221.
 2009 09  94228·
 2009 10  6162·
 2009 11  12191·
 2009 12  40159·
 2010 01 73203·
 2010 02 28162·
 2010 03 56204.
 2010 04 68245.
 2010 05 86207.
 2010 06 23182·
 2010 07 82194·
 2010 08 81219.
 2010 09 9197.
 2010 10 97227.
 2010 11 26204·
 2010 12 48180.
 2011 01  41190·
 2011 02  82214.
 2011 03  53234·
 2011 04  64216.
 2011 05  8213·
 2011 06  33216·
 2011 07  48202.
 2011 08  47189.
 2011 09  61212·
 2011 10  34201.
 2011 11  27228.
 2011 12  42228·
 2012 01 74226.
 2012 02 90268.
 2012 03 26248.
 2012 04 17242.
 2012 05 49255·
 2012 06 33214·
 2012 07 8241.
 2012 08 67230·
 2012 09 11255.
 2012 10 20218.
 2012 11 61268.
 2012 12 11323.
 2013 01  9300·
 2013 02  32335.
 2013 03  99274·
 2013 04  94229.
 2013 05  20300.
 2013 06  77280·
 2013 07  58278·
 2013 08  83253.
 2013 09  44245·
 2013 10  85218·
 2013 11  3248.
 2013 12  74247.
 2014 01 6226·
 2014 02 13316·
 2014 03 20333.
 2014 04 86297·
 2014 05 57328·
 2014 06 44290·
 2014 07 23243.
 2014 08 62264·
 2014 09 71243·
 2014 10 83289·
 2014 11 49278·
 2014 12 72226.
 2015 01  50251.
 2015 02  62244·
 2015 03  62249·
 2015 04  9290·
 2015 05  19260·
 2015 06  38262·
 2015 07  50269·
 2015 08  94245·
 2015 09  28311·
 2015 10  93284·
 2015 11  24265.
 2015 12  71321·
 2016 01 52268.
 2016 02 33253.
 2016 03 24303·
 2016 04 7264.
 2016 05 93276.
 2016 06 90299·
 2016 07 11386·
 2016 08 99374.
 2016 09 75361·
 2016 10 20297.
 2016 11 75304·
 2016 12 63307.
 2017 01  48297.
 2017 02  6317.
 2017 03  27344·
 2017 04  46366·
 2017 05  89360·
 2017 06  53289.


 2017 07  6258.
 2017 08  15231.
 2017 09  97212·
 2017 10  93328.
 2017 11  75280.
 2017 12  66365.
 2018 01 98315.
 2018 02 84350.
 2018 03 21299.
 2018 04 17276·
 2018 05 42285·
 2018 06 6278·
 2018 07 57300·
 2018 08 12296.
 2018 09 5314·
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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: 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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