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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 29743·
 2000 02 97743·
 2000 03 7730.
 2000 04 41705.
 2000 05 8683·
 2000 06 18664.
 2000 07 83674·
 2000 08 46750.
 2000 09 29693·
 2000 10 12735.
 2000 11 36743·
 2000 12 25706.
 2001 01  42729.
 2001 02  62761·
 2001 03  77819.
 2001 04  22769·
 2001 05  21765.
 2001 06  73704·
 2001 07  46686·
 2001 08  5691·
 2001 09  68661.
 2001 10  78612·
 2001 11  3561.
 2001 12  70580.
 2002 01 9558·
 2002 02 32587·
 2002 03 38635·
 2002 04 35601·
 2002 05 92506·
 2002 06 19553.
 2002 07 64552.
 2002 08 44553.
 2002 09 94639.
 2002 10 43660·
 2002 11 18586·
 2002 12 67683·
 2003 01  15555.
 2003 02  38537·
 2003 03  63566·
 2003 04  97553·
 2003 05  81620·
 2003 06  59563·
 2003 07  87531·
 2003 08  55515.
 2003 09  41547.
 2003 10  88553·
 2003 11  2613.
 2003 12  83665.
 2004 01 72557.
 2004 02 32511.
 2004 03 48486.
 2004 04 51518.
 2004 05 73511.
 2004 06 23552.
 2004 07 86564·
 2004 08 54519·
 2004 09 71541·
 2004 10 17598·
 2004 11 5635.
 2004 12 9641.
 2005 01  15624·
 2005 02  96559.
 2005 03  18575.
 2005 04  63628·
 2005 05  80602·
 2005 06  66631.
 2005 07  62575·
 2005 08  83536.
 2005 09  68581.
 2005 10  59586.
 2005 11  0589·
 2005 12  63624·
 2006 01 3605·
 2006 02 32608.
 2006 03 20686·
 2006 04 24682.
 2006 05 37607.
 2006 06 67583.
 2006 07 36575.
 2006 08 9578·
 2006 09 44602.
 2006 10 69614·
 2006 11 84549·
 2006 12 86562·
 2007 01  24533·
 2007 02  71567·
 2007 03  28617.
 2007 04  52579·
 2007 05  4597.
 2007 06  29584·
 2007 07  56556·
 2007 08  23526.
 2007 09  33492.
 2007 10  25552.
 2007 11  80585.
 2007 12  46600·
 2008 01 87566.
 2008 02 66614·
 2008 03 39652.
 2008 04 88658·
 2008 05 67715.
 2008 06 83675·
 2008 07 95632.
 2008 08 44645·
 2008 09 97609·
 2008 10 33603·
 2008 11 37645·
 2008 12 33622.
 2009 01  28576·
 2009 02  97529·
 2009 03  77491.
 2009 04  99560·
 2009 05  36596·
 2009 06  82532.
 2009 07  53564·
 2009 08  11539·
 2009 09  21408.
 2009 10  20445·
 2009 11  28503·
 2009 12  64505·
 2010 01 7510·
 2010 02 68548.
 2010 03 89549·
 2010 04 77581.
 2010 05 47545.
 2010 06 6520·
 2010 07 51507.
 2010 08 93487·
 2010 09 15550.
 2010 10 43536.
 2010 11 50509.
 2010 12 82603.
 2011 01  11678·
 2011 02  8647.
 2011 03  49676·
 2011 04  38605.
 2011 05  61551.
 2011 06  60579.
 2011 07  37607.
 2011 08  81567·
 2011 09  15578.
 2011 10  79543.
 2011 11  26479·
 2011 12  53543.
 2012 01 49582·
 2012 02 72553·
 2012 03 55597·
 2012 04 25622·
 2012 05 63636·
 2012 06 72615·
 2012 07 85693·
 2012 08 91602·
 2012 09 82632.
 2012 10 34640·
 2012 11 6592.
 2012 12 69602.
 2013 01  57564.
 2013 02  40540.
 2013 03  29542·
 2013 04  5609.
 2013 05  63739·
 2013 06  96758·
 2013 07  93761.
 2013 08  66786·
 2013 09  1779·
 2013 10  36718·
 2013 11  61667.
 2013 12  47662·
 2014 01 96683.
 2014 02 14593.
 2014 03 20590·
 2014 04 68627·
 2014 05 98679·
 2014 06 13691.
 2014 07 84752·
 2014 08 72744·
 2014 09 83645.
 2014 10 40652.
 2014 11 90647.
 2014 12 29636.
 2015 01  50668.
 2015 02  25669.
 2015 03  1648·
 2015 04  33627.
 2015 05  27701·
 2015 06  26724.
 2015 07  6707·
 2015 08  2765·
 2015 09  62690·
 2015 10  25620·
 2015 11  16664·
 2015 12  81574·
 2016 01 32589·
 2016 02 27608·
 2016 03 70680.
 2016 04 39706·
 2016 05 37748·
 2016 06 65750.
 2016 07 31732.
 2016 08 71730·
 2016 09 1681·
 2016 10 95652·
 2016 11 87670·
 2016 12 95733.
 2017 01  76725·
 2017 02  99741.
 2017 03  50763.
 2017 04  56777·
 2017 05  37799·


 2017 06  84765.
 2017 07  59767·
 2017 08  22718.
 2017 09  84637.
 2017 10  80685.
 2017 11  76681·
 2017 12  88658.
 2018 01 43692.
 2018 02 46783·
 2018 03 89779.
 2018 04 74813·
 2018 05 64817·
 2018 06 62726·
 2018 07 11744·
 2018 08 22719.
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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

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