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 Series Title: Employed: Durable goods manufacturing, 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 16743·
 2000 02 22743·
 2000 03 57730·
 2000 04 67705.
 2000 05 24683·
 2000 06 0664.
 2000 07 69674·
 2000 08 36750·
 2000 09 87693·
 2000 10 64735.
 2000 11 69743.
 2000 12 91706·
 2001 01  54729.
 2001 02  96761.
 2001 03  71819.
 2001 04  76769.
 2001 05  0765·
 2001 06  2704·
 2001 07  12686.
 2001 08  61691.
 2001 09  26661.
 2001 10  13612·
 2001 11  55561·
 2001 12  39580.
 2002 01 58558.
 2002 02 88587.
 2002 03 88635·
 2002 04 30601.
 2002 05 45506.
 2002 06 6553.
 2002 07 24552·
 2002 08 78553·
 2002 09 64639.
 2002 10 75660.
 2002 11 1586·
 2002 12 51683·
 2003 01  14555.
 2003 02  27537.
 2003 03  81566.
 2003 04  45553·
 2003 05  22620·
 2003 06  18563.
 2003 07  53531·
 2003 08  79515·
 2003 09  36547.
 2003 10  30553·
 2003 11  29613.
 2003 12  95665.
 2004 01 33557.
 2004 02 69511.
 2004 03 47486.
 2004 04 64518.
 2004 05 14511·
 2004 06 67552.
 2004 07 71564.
 2004 08 80519·
 2004 09 3541·
 2004 10 80598·
 2004 11 88635.
 2004 12 62641·
 2005 01  51624·
 2005 02  91559·
 2005 03  11575·
 2005 04  54628.
 2005 05  33602.
 2005 06  6631.
 2005 07  78575.
 2005 08  25536·
 2005 09  50581·
 2005 10  57586·
 2005 11  51589·
 2005 12  69624·
 2006 01 27605.
 2006 02 99608·
 2006 03 19686.
 2006 04 6682.
 2006 05 14607.
 2006 06 16583·
 2006 07 95575·
 2006 08 79578·
 2006 09 88602.
 2006 10 13614.
 2006 11 16549.
 2006 12 58562·
 2007 01  47533·
 2007 02  22567.
 2007 03  45617.
 2007 04  36579.
 2007 05  19597·
 2007 06  0584.
 2007 07  71556·
 2007 08  34526.
 2007 09  52492·
 2007 10  28552·
 2007 11  6585·
 2007 12  95600.
 2008 01 23566.
 2008 02 14614·
 2008 03 88652·
 2008 04 88658.
 2008 05 31715.
 2008 06 88675.
 2008 07 79632.
 2008 08 7645·
 2008 09 3609·
 2008 10 7603·
 2008 11 69645·
 2008 12 72622.
 2009 01  89576.
 2009 02  54529.
 2009 03  69491·
 2009 04  27560.
 2009 05  63596.
 2009 06  34532·
 2009 07  18564·
 2009 08  40539·
 2009 09  27408·
 2009 10  79445·
 2009 11  78503·
 2009 12  7505·
 2010 01 5510.
 2010 02 47548.
 2010 03 37549·
 2010 04 45581·
 2010 05 49545·
 2010 06 17520·
 2010 07 9507·
 2010 08 0487·
 2010 09 33550.
 2010 10 98536·
 2010 11 31509.
 2010 12 40603·
 2011 01  58678.
 2011 02  21647·
 2011 03  66676.
 2011 04  60605.
 2011 05  50551.
 2011 06  43579·
 2011 07  2607·
 2011 08  78567·
 2011 09  58578.
 2011 10  44543.
 2011 11  51479.
 2011 12  39543.
 2012 01 59582·
 2012 02 32553·
 2012 03 53597·
 2012 04 12622·
 2012 05 52636·
 2012 06 39615.
 2012 07 69693·
 2012 08 91602.
 2012 09 62632.
 2012 10 20640·
 2012 11 87592.
 2012 12 96602.
 2013 01  42564.
 2013 02  58540·
 2013 03  21542·
 2013 04  69609.
 2013 05  64739.
 2013 06  60758·
 2013 07  8761.
 2013 08  82786·
 2013 09  31779.
 2013 10  57718.
 2013 11  11667·
 2013 12  27662.
 2014 01 68683.
 2014 02 5593·
 2014 03 18590·
 2014 04 23627·
 2014 05 24679.
 2014 06 86691·
 2014 07 42752.
 2014 08 16744.
 2014 09 75645·
 2014 10 7652·
 2014 11 21647.
 2014 12 74636·
 2015 01  22668.
 2015 02  0669.
 2015 03  17648.
 2015 04  91627·
 2015 05  90701.
 2015 06  21724·
 2015 07  20707·
 2015 08  86765·
 2015 09  30690.
 2015 10  51620.
 2015 11  40664.
 2015 12  4574·
 2016 01 16589·
 2016 02 99608·
 2016 03 17680.
 2016 04 13706.
 2016 05 50748.
 2016 06 94750·
 2016 07 14732·
 2016 08 8730.
 2016 09 56681·
 2016 10 94652.
 2016 11 17670.
 2016 12 8733.
 2017 01  85725.
 2017 02  80741.


 2017 03  41763·
 2017 04  57777·
 2017 05  12799.
 2017 06  59765.
 2017 07  22767·
 2017 08  25718·
 2017 09  39637·
 2017 10  63685.
 2017 11  25681.
 2017 12  4658·
 2018 01 89692.
 2018 02 48783·
 2018 03 36779·
 2018 04 15813·
 2018 05 14817·
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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: Employed: Durable goods manufacturing, 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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