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 Series Title: Employment Level: Multiple Jobholders, Asian Men: 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 25111·
 2000 02 8599.
 2000 03 90117.
 2000 04 0142.
 2000 05 9895.
 2000 06 68128·
 2000 07 98132·
 2000 08 5116·
 2000 09 87137.
 2000 10 99112·
 2000 11 57128·
 2000 12 59117.
 2001 01  43113·
 2001 02  61119·
 2001 03  79148.
 2001 04  5164.
 2001 05  41121.
 2001 06  59154·
 2001 07  3112·
 2001 08  13119·
 2001 09  82138·
 2001 10  26128·
 2001 11  91108·
 2001 12  77105.
 2002 01 90100.
 2002 02 18131.
 2002 03 32151.
 2002 04 17134.
 2002 05 17116.
 2002 06 16125·
 2002 07 39116.
 2002 08 76106·
 2002 09 37118.
 2002 10 2899·
 2002 11 48116.
 2002 12 23105.
 2003 01  5277·
 2003 02  84106.
 2003 03  24103.
 2003 04  5399·
 2003 05  86117.
 2003 06  4387·
 2003 07  5495·
 2003 08  85103·
 2003 09  90105·
 2003 10  8480.
 2003 11  5177·
 2003 12  6399·
 2004 01 3982.
 2004 02 16115·
 2004 03 52118.
 2004 04 56105·
 2004 05 34113.
 2004 06 68119·
 2004 07 21135.
 2004 08 58115.
 2004 09 99103.
 2004 10 9998·
 2004 11 46156·
 2004 12 88155·
 2005 01  86133.
 2005 02  90148.
 2005 03  40106.
 2005 04  9184.
 2005 05  7092·
 2005 06  48109.
 2005 07  39123.
 2005 08  36134·
 2005 09  52129.
 2005 10  3177.
 2005 11  8154·
 2005 12  16152.
 2006 01 55155.
 2006 02 13150·
 2006 03 34118.
 2006 04 51135.
 2006 05 32113.
 2006 06 59133.
 2006 07 31134·
 2006 08 86122·
 2006 09 57115.
 2006 10 49114·
 2006 11 35106·
 2006 12 88125·
 2007 01  31116·
 2007 02  13144.
 2007 03  10155.
 2007 04  53106.
 2007 05  79124.
 2007 06  8109·
 2007 07  43135·
 2007 08  99117·
 2007 09  52103.
 2007 10  1697·
 2007 11  4995.
 2007 12  71133·
 2008 01 24102·
 2008 02 44131.
 2008 03 64132·
 2008 04 38144·
 2008 05 97126.
 2008 06 23115.
 2008 07 51109.
 2008 08 93136.
 2008 09 96118·
 2008 10 10104·
 2008 11 9890·
 2008 12 57109.
 2009 01  70111·
 2009 02  8697·
 2009 03  19105.
 2009 04  73127·
 2009 05  96142.
 2009 06  59124·
 2009 07  5183·
 2009 08  10107·
 2009 09  74128.
 2009 10  5996·
 2009 11  56104·
 2009 12  62106.
 2010 01 30101·
 2010 02 4479·
 2010 03 24113·
 2010 04 49119·
 2010 05 1388.
 2010 06 9590·
 2010 07 6674.
 2010 08 1580.
 2010 09 9991·
 2010 10 18117·
 2010 11 2190.
 2010 12 29107·
 2011 01  8896·
 2011 02  46101·
 2011 03  51106.
 2011 04  8598.
 2011 05  799.
 2011 06  3492.
 2011 07  45109·
 2011 08  2120.
 2011 09  497.
 2011 10  6690·
 2011 11  1595.
 2011 12  2499·
 2012 01 5693.
 2012 02 46118.
 2012 03 0106·
 2012 04 21100.
 2012 05 63128·
 2012 06 8116.
 2012 07 61115·
 2012 08 86118.
 2012 09 51123.
 2012 10 690·
 2012 11 87123.
 2012 12 39158·
 2013 01  69135.
 2013 02  25160.
 2013 03  92128.
 2013 04  24110.
 2013 05  94132.
 2013 06  69122·
 2013 07  12122.
 2013 08  10108·
 2013 09  25100.
 2013 10  70106.
 2013 11  10113·
 2013 12  9186.
 2014 01 8884.
 2014 02 85135·
 2014 03 75161.
 2014 04 86169.
 2014 05 34182·
 2014 06 97147.
 2014 07 20110·
 2014 08 40124.
 2014 09 37105·
 2014 10 10134.
 2014 11 82124·
 2014 12 21118.
 2015 01  98119·
 2015 02  5899·
 2015 03  2494.
 2015 04  24121·
 2015 05  4396.
 2015 06  96117.
 2015 07  34139·
 2015 08  68130·
 2015 09  22156·
 2015 10  7131.
 2015 11  25120·
 2015 12  97127·
 2016 01 10150.
 2016 02 96113.
 2016 03 35138.
 2016 04 80109·
 2016 05 8114·
 2016 06 96142·
 2016 07 27172.
 2016 08 11161·
 2016 09 40182.
 2016 10 63146.
 2016 11 89135·
 2016 12 10158.
 2017 01  59152.
 2017 02  80165.
 2017 03  33187.
 2017 04  20174·
 2017 05  38186·
 2017 06  51160.


 2017 07  97128.
 2017 08  11102·
 2017 09  7884·
 2017 10  10188.
 2017 11  45142.
 2017 12  77179.
 2018 01 6178.
 2018 02 13183.
 2018 03 64155·
 2018 04 37164·
 2018 05 70167.
 2018 06 41142·
 2018 07 67146·
 2018 08 35155.
 2018 09 46165·
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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 Men: 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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