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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 37247.
 2000 02 9222.
 2000 03 87250.
 2000 04 6288.
 2000 05 23206.
 2000 06 99225.
 2000 07 96244·
 2000 08 6205·
 2000 09 1251·
 2000 10 13225·
 2000 11 31257·
 2000 12 29241·
 2001 01  21246·
 2001 02  32252.
 2001 03  4243.
 2001 04  20276·
 2001 05  58228.
 2001 06  63265·
 2001 07  54227.
 2001 08  48240.
 2001 09  12252.
 2001 10  37241·
 2001 11  44248.
 2001 12  8226.
 2002 01 9235.
 2002 02 11277·
 2002 03 61270.
 2002 04 17269·
 2002 05 99243.
 2002 06 67248.
 2002 07 19234·
 2002 08 21206·
 2002 09 58222.
 2002 10 11205.
 2002 11 54260.
 2002 12 88236·
 2003 01  87187.
 2003 02  75198.
 2003 03  31199.
 2003 04  13195.
 2003 05  9240.
 2003 06  16217·
 2003 07  37202.
 2003 08  15196.
 2003 09  77190.
 2003 10  15154.
 2003 11  85170.
 2003 12  38206·
 2004 01 65192·
 2004 02 78276.
 2004 03 13231·
 2004 04 50248·
 2004 05 73221.
 2004 06 39194.
 2004 07 83215·
 2004 08 47194·
 2004 09 27198.
 2004 10 52191.
 2004 11 84278·
 2004 12 48274·
 2005 01  78257.
 2005 02  0281·
 2005 03  29226·
 2005 04  96223·
 2005 05  1213·
 2005 06  90277.
 2005 07  55239.
 2005 08  60264.
 2005 09  96251.
 2005 10  53320·
 2005 11  25269.
 2005 12  35261·
 2006 01 88262.
 2006 02 45282.
 2006 03 27253·
 2006 04 40233.
 2006 05 29239.
 2006 06 49243.
 2006 07 75242·
 2006 08 20243.
 2006 09 92203.
 2006 10 71250.
 2006 11 5239.
 2006 12 42295.
 2007 01  80276·
 2007 02  42312·
 2007 03  81284·
 2007 04  2247.
 2007 05  17254·
 2007 06  20216·
 2007 07  91253·
 2007 08  18239.
 2007 09  53237·
 2007 10  86220·
 2007 11  47220·
 2007 12  35235·
 2008 01 64218·
 2008 02 46266·
 2008 03 88283·
 2008 04 21306.
 2008 05 51263·
 2008 06 33266.
 2008 07 77262·
 2008 08 72287·
 2008 09 38248.
 2008 10 2213·
 2008 11 0200.
 2008 12 5234.
 2009 01  76213.
 2009 02  36210·
 2009 03  72212.
 2009 04  66248·
 2009 05  41262.
 2009 06  41236.
 2009 07  30183·
 2009 08  23221·
 2009 09  33228.
 2009 10  48162·
 2009 11  37191.
 2009 12  71159·
 2010 01 77203·
 2010 02 15162.
 2010 03 81204·
 2010 04 28245·
 2010 05 23207.
 2010 06 23182·
 2010 07 74194·
 2010 08 38219.
 2010 09 48197·
 2010 10 79227·
 2010 11 55204.
 2010 12 72180·
 2011 01  51190·
 2011 02  14214.
 2011 03  87234·
 2011 04  23216·
 2011 05  58213.
 2011 06  85216·
 2011 07  57202.
 2011 08  10189.
 2011 09  19212.
 2011 10  74201.
 2011 11  78228.
 2011 12  77228.
 2012 01 10226.
 2012 02 87268·
 2012 03 88248·
 2012 04 94242.
 2012 05 31255.
 2012 06 56214.
 2012 07 51241.
 2012 08 54230.
 2012 09 7255.
 2012 10 37218·
 2012 11 54268.
 2012 12 77323.
 2013 01  89300.
 2013 02  13335.
 2013 03  9274·
 2013 04  6229·
 2013 05  53300.
 2013 06  89280.
 2013 07  55278.
 2013 08  12253.
 2013 09  97245·
 2013 10  98218·
 2013 11  55248.
 2013 12  88247.
 2014 01 49226.
 2014 02 96316·
 2014 03 96333·
 2014 04 54297·
 2014 05 58328·
 2014 06 64290·
 2014 07 92243·
 2014 08 52264.
 2014 09 0243·
 2014 10 10289.
 2014 11 80278.
 2014 12 53226.
 2015 01  75251.
 2015 02  66244.
 2015 03  23249·
 2015 04  51290.
 2015 05  9260·
 2015 06  86262.
 2015 07  10269·
 2015 08  65245·
 2015 09  51311·
 2015 10  54284·
 2015 11  52265.
 2015 12  39321.
 2016 01 78268.
 2016 02 76253.
 2016 03 88303.
 2016 04 42264·
 2016 05 89276.
 2016 06 84299.
 2016 07 81386.
 2016 08 68374.
 2016 09 11361.
 2016 10 33297·
 2016 11 19304.
 2016 12 37307.
 2017 01  93297·
 2017 02  7317·
 2017 03  14344.
 2017 04  92366.


 2017 05  11360·
 2017 06  11289.
 2017 07  5258·
 2017 08  3231·
 2017 09  65212.
 2017 10  77328.
 2017 11  54280.
 2017 12  64365.
 2018 01 81315.
 2018 02 62350.
 2018 03 49299·
 2018 04 93276.
 2018 05 8285.
 2018 06 48278.
 2018 07 3300.
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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

New data set: Quarterly Financial Reporting: Manufacturing, Mining, Trade, and Selected Service Industries

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