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 Series Title: Employment Level: Multiple Jobholders, Asian: NSA
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 2000 01 43247·
 2000 02 95222·
 2000 03 94250.
 2000 04 28288·
 2000 05 13206.
 2000 06 65225·
 2000 07 2244·
 2000 08 72205·
 2000 09 6251·
 2000 10 89225.
 2000 11 67257·
 2000 12 72241.
 2001 01  72246.
 2001 02  49252.
 2001 03  2243.
 2001 04  70276.
 2001 05  86228.
 2001 06  53265·
 2001 07  45227·
 2001 08  36240·
 2001 09  49252·
 2001 10  31241·
 2001 11  59248.
 2001 12  65226.
 2002 01 86235·
 2002 02 40277·
 2002 03 32270·
 2002 04 76269·
 2002 05 47243·
 2002 06 62248·
 2002 07 76234·
 2002 08 12206.
 2002 09 9222·
 2002 10 4205.
 2002 11 30260.
 2002 12 42236.
 2003 01  71187·
 2003 02  97198.
 2003 03  57199·
 2003 04  62195·
 2003 05  58240.
 2003 06  98217.
 2003 07  43202·
 2003 08  90196·
 2003 09  22190·
 2003 10  89154·
 2003 11  3170·
 2003 12  69206.
 2004 01 37192·
 2004 02 75276.
 2004 03 74231·
 2004 04 71248.
 2004 05 4221·
 2004 06 90194·
 2004 07 18215.
 2004 08 87194.
 2004 09 49198·
 2004 10 88191.
 2004 11 25278.
 2004 12 38274.
 2005 01  21257·
 2005 02  53281.
 2005 03  6226.
 2005 04  68223.
 2005 05  96213.
 2005 06  91277.
 2005 07  0239·
 2005 08  46264·
 2005 09  74251·
 2005 10  32320.
 2005 11  70269.
 2005 12  66261.
 2006 01 82262·
 2006 02 35282·
 2006 03 3253.
 2006 04 47233.
 2006 05 68239·
 2006 06 80243.
 2006 07 12242·
 2006 08 33243·
 2006 09 10203.
 2006 10 75250·
 2006 11 35239·
 2006 12 94295.
 2007 01  6276·
 2007 02  50312.
 2007 03  36284.
 2007 04  24247·
 2007 05  83254·
 2007 06  63216·
 2007 07  1253·
 2007 08  41239·
 2007 09  90237·
 2007 10  96220·
 2007 11  44220·
 2007 12  90235·
 2008 01 4218.
 2008 02 54266·
 2008 03 3283.
 2008 04 39306·
 2008 05 24263.
 2008 06 69266.
 2008 07 41262.
 2008 08 85287·
 2008 09 76248·
 2008 10 99213.
 2008 11 45200.
 2008 12 44234.
 2009 01  10213·
 2009 02  24210.
 2009 03  29212.
 2009 04  62248·
 2009 05  3262·
 2009 06  52236.
 2009 07  30183.
 2009 08  7221.
 2009 09  53228.
 2009 10  13162·
 2009 11  11191.
 2009 12  74159.
 2010 01 87203·
 2010 02 66162.
 2010 03 60204·
 2010 04 82245.
 2010 05 55207·
 2010 06 90182.
 2010 07 90194.
 2010 08 75219.
 2010 09 32197·
 2010 10 94227·
 2010 11 40204·
 2010 12 22180.
 2011 01  19190·
 2011 02  8214·
 2011 03  71234.
 2011 04  18216·
 2011 05  41213.
 2011 06  89216.
 2011 07  71202·
 2011 08  80189·
 2011 09  48212.
 2011 10  19201.
 2011 11  54228.
 2011 12  55228·
 2012 01 16226.
 2012 02 5268.
 2012 03 58248·
 2012 04 10242·
 2012 05 46255·
 2012 06 78214·
 2012 07 45241·
 2012 08 40230.
 2012 09 62255·
 2012 10 95218·
 2012 11 3268.
 2012 12 63323.
 2013 01  15300·
 2013 02  37335·
 2013 03  45274·
 2013 04  25229.
 2013 05  81300.
 2013 06  11280.
 2013 07  9278·
 2013 08  94253·
 2013 09  60245·
 2013 10  49218·
 2013 11  58248.
 2013 12  65247·
 2014 01 76226.
 2014 02 7316.
 2014 03 80333.
 2014 04 56297·
 2014 05 82328.
 2014 06 67290.
 2014 07 88243·
 2014 08 12264·
 2014 09 51243·
 2014 10 36289.
 2014 11 19278·
 2014 12 2226·
 2015 01  85251.
 2015 02  45244·
 2015 03  36249·
 2015 04  19290.
 2015 05  8260.
 2015 06  51262·
 2015 07  28269·
 2015 08  84245·
 2015 09  72311·
 2015 10  35284·
 2015 11  8265.
 2015 12  40321.
 2016 01 51268·
 2016 02 5253.
 2016 03 12303·
 2016 04 56264.
 2016 05 46276.
 2016 06 91299·
 2016 07 4386·
 2016 08 27374.
 2016 09 83361.
 2016 10 51297.
 2016 11 72304·
 2016 12 71307.
 2017 01  11297.
 2017 02  66317.


 2017 03  29344·
 2017 04  34366.
 2017 05  6360.
 2017 06  43289.
 2017 07  13258.
 2017 08  83231·
 2017 09  69212·
 2017 10  13328·
 2017 11  86280.
 2017 12  13365·
 2018 01 25315·
 2018 02 33350.
 2018 03 37299·
 2018 04 44276·
 2018 05 24285·
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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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