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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 30247·
 2000 02 49222·
 2000 03 56250.
 2000 04 85288·
 2000 05 93206·
 2000 06 41225·
 2000 07 91244.
 2000 08 36205·
 2000 09 47251.
 2000 10 56225·
 2000 11 53257·
 2000 12 11241·
 2001 01  44246·
 2001 02  77252·
 2001 03  53243·
 2001 04  54276.
 2001 05  57228.
 2001 06  9265·
 2001 07  29227·
 2001 08  33240·
 2001 09  88252.
 2001 10  85241·
 2001 11  46248·
 2001 12  44226·
 2002 01 61235.
 2002 02 61277.
 2002 03 89270·
 2002 04 5269·
 2002 05 28243.
 2002 06 18248·
 2002 07 73234·
 2002 08 60206·
 2002 09 64222.
 2002 10 64205.
 2002 11 36260·
 2002 12 79236·
 2003 01  69187.
 2003 02  29198·
 2003 03  39199.
 2003 04  56195·
 2003 05  68240·
 2003 06  72217·
 2003 07  72202·
 2003 08  9196·
 2003 09  12190.
 2003 10  72154.
 2003 11  46170.
 2003 12  84206·
 2004 01 76192·
 2004 02 37276·
 2004 03 1231.
 2004 04 48248·
 2004 05 61221·
 2004 06 99194.
 2004 07 98215.
 2004 08 96194·
 2004 09 92198.
 2004 10 14191·
 2004 11 25278·
 2004 12 48274·
 2005 01  20257·
 2005 02  64281.
 2005 03  96226.
 2005 04  48223.
 2005 05  19213.
 2005 06  55277.
 2005 07  49239.
 2005 08  64264.
 2005 09  90251·
 2005 10  20320·
 2005 11  45269.
 2005 12  91261.
 2006 01 59262·
 2006 02 14282·
 2006 03 74253.
 2006 04 47233.
 2006 05 76239.
 2006 06 19243.
 2006 07 48242·
 2006 08 78243.
 2006 09 17203.
 2006 10 43250·
 2006 11 5239·
 2006 12 52295·
 2007 01  81276·
 2007 02  16312.
 2007 03  8284·
 2007 04  63247·
 2007 05  94254·
 2007 06  95216·
 2007 07  44253.
 2007 08  31239·
 2007 09  7237·
 2007 10  62220·
 2007 11  27220·
 2007 12  99235·
 2008 01 95218.
 2008 02 24266.
 2008 03 95283.
 2008 04 38306.
 2008 05 58263.
 2008 06 12266·
 2008 07 10262.
 2008 08 40287·
 2008 09 22248·
 2008 10 83213·
 2008 11 60200.
 2008 12 25234·
 2009 01  36213·
 2009 02  18210.
 2009 03  58212·
 2009 04  37248.
 2009 05  78262.
 2009 06  25236·
 2009 07  43183·
 2009 08  45221.
 2009 09  46228·
 2009 10  34162·
 2009 11  76191·
 2009 12  44159.
 2010 01 67203·
 2010 02 2162·
 2010 03 46204·
 2010 04 53245·
 2010 05 90207.
 2010 06 12182·
 2010 07 66194·
 2010 08 15219.
 2010 09 91197·
 2010 10 69227.
 2010 11 74204·
 2010 12 1180.
 2011 01  71190·
 2011 02  6214·
 2011 03  32234·
 2011 04  3216.
 2011 05  54213.
 2011 06  79216·
 2011 07  29202·
 2011 08  41189·
 2011 09  92212.
 2011 10  69201.
 2011 11  77228.
 2011 12  60228.
 2012 01 59226·
 2012 02 84268.
 2012 03 14248·
 2012 04 28242.
 2012 05 57255·
 2012 06 54214·
 2012 07 3241.
 2012 08 40230·
 2012 09 10255·
 2012 10 37218·
 2012 11 32268.
 2012 12 15323·
 2013 01  68300·
 2013 02  14335·
 2013 03  14274.
 2013 04  96229.
 2013 05  8300·
 2013 06  92280.
 2013 07  86278.
 2013 08  53253.
 2013 09  29245·
 2013 10  2218·
 2013 11  13248·
 2013 12  81247·
 2014 01 58226·
 2014 02 2316.
 2014 03 81333·
 2014 04 98297·
 2014 05 43328·
 2014 06 72290·
 2014 07 3243.
 2014 08 48264.
 2014 09 62243·
 2014 10 20289.
 2014 11 18278.
 2014 12 1226·
 2015 01  13251.
 2015 02  76244·
 2015 03  88249.
 2015 04  50290·
 2015 05  24260·
 2015 06  98262·
 2015 07  0269.
 2015 08  16245·
 2015 09  43311·
 2015 10  68284·
 2015 11  69265.
 2015 12  41321.
 2016 01 46268.
 2016 02 91253·
 2016 03 32303·
 2016 04 96264.
 2016 05 34276.
 2016 06 0299·
 2016 07 52386.
 2016 08 73374·
 2016 09 32361·
 2016 10 52297·
 2016 11 16304·
 2016 12 94307·
 2017 01  91297·
 2017 02  27317·
 2017 03  38344·
 2017 04  0366·
 2017 05  85360.
 2017 06  33289·
 2017 07  55258.
 2017 08  63231.
 2017 09  16212·


 2017 10  0328.
 2017 11  31280·
 2017 12  75365.
 2018 01 8315·
 2018 02 87350·
 2018 03 52299·
 2018 04 56276.
 2018 05 12285.
 2018 06 74278.
 2018 07 33300·
 2018 08 51296·
 2018 09 4314·
 2018 10 68297.
 2018 11 11314·
 2018 12 27363·
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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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