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 Series Title: Persons At Work in Durable Goods Manufacturing Industries, Wage and Salary Workers: 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 3812222·
 2000 02 7612192.
 2000 03 3112312·
 2000 04 8112345.
 2000 05 2812118·
 2000 06 7511911.
 2000 07 2811283·
 2000 08 2411535·
 2000 09 7811684·
 2000 10 6611822·
 2000 11 2011789·
 2000 12 5911936.
 2001 01  3911684·
 2001 02  3111677.
 2001 03  1911688.
 2001 04  3111466.
 2001 05  8611511·
 2001 06  7611209.
 2001 07  6410605.
 2001 08  810697.
 2001 09  1910783.
 2001 10  3410862·
 2001 11  1610597.
 2001 12  8510777·
 2002 01 6410534·
 2002 02 6010548.
 2002 03 6610622·
 2002 04 8110473.
 2002 05 7110406.
 2002 06 3710151.
 2002 07 249858.
 2002 08 4010111·
 2002 09 1510130·
 2002 10 7110477.
 2002 11 2910364.
 2002 12 3210447.
 2003 01  9710475·
 2003 02  9410434·
 2003 03  4410095·
 2003 04  5010020·
 2003 05  429981·
 2003 06  629931.
 2003 07  579291.
 2003 08  139809·
 2003 09  19810·
 2003 10  579948·
 2003 11  8110193.
 2003 12  6610201·
 2004 01 499982·
 2004 02 859971·
 2004 03 539678.
 2004 04 789827·
 2004 05 869825·
 2004 06 799681.
 2004 07 369499.
 2004 08 439886.
 2004 09 389940·
 2004 10 959806·
 2004 11 199889·
 2004 12 8010076.
 2005 01  5510015·
 2005 02  149805.
 2005 03  159887·
 2005 04  339912.
 2005 05  139745·
 2005 06  439863.
 2005 07  609392.
 2005 08  719461.
 2005 09  119828.
 2005 10  159920·
 2005 11  1810052.
 2005 12  9010302.
 2006 01 7610307·
 2006 02 8410256·
 2006 03 7710403·
 2006 04 610130·
 2006 05 5810034·
 2006 06 3410102·
 2006 07 519752.
 2006 08 669705·
 2006 09 329921·
 2006 10 719950.
 2006 11 759710·
 2006 12 379943·
 2007 01  989661·
 2007 02  2610005·
 2007 03  159941·
 2007 04  159853·
 2007 05  8310115.
 2007 06  569717.
 2007 07  569519·
 2007 08  189649·
 2007 09  359809·
 2007 10  429967·
 2007 11  1410146.
 2007 12  9010105.
 2008 01 319892.
 2008 02 929820.
 2008 03 249867·
 2008 04 19967·
 2008 05 729790·
 2008 06 3710044·
 2008 07 519617.
 2008 08 449806·
 2008 09 819880·
 2008 10 349770.
 2008 11 819840.
 2008 12 399528.
 2009 01  119073.
 2009 02  648978.
 2009 03  298588.
 2009 04  308554.
 2009 05  368593.
 2009 06  338342·
 2009 07  318375.
 2009 08  868463.
 2009 09  568377.
 2009 10  748445.
 2009 11  518305·
 2009 12  28028·
 2010 01 987984.
 2010 02 448048·
 2010 03 778112·
 2010 04 958336.
 2010 05 118518.
 2010 06 238517·
 2010 07 218625.
 2010 08 128597.
 2010 09 718629.
 2010 10 188550.
 2010 11 218524.
 2010 12 198568·
 2011 01  788591·
 2011 02  628390.
 2011 03  418580.
 2011 04  138632.
 2011 05  578526·
 2011 06  108733.
 2011 07  688477·
 2011 08  128519.
 2011 09  608859·
 2011 10  458697.
 2011 11  158631.
 2011 12  598940·
 2012 01 618709.
 2012 02 738837·
 2012 03 208685.
 2012 04 258779·
 2012 05 608759·
 2012 06 258899.
 2012 07 468846·
 2012 08 38804.
 2012 09 849037·
 2012 10 599074.
 2012 11 809073.
 2012 12 128862·
 2013 01  828808·
 2013 02  558833.
 2013 03  368839·
 2013 04  988789.
 2013 05  318746·
 2013 06  218890.
 2013 07  528930·
 2013 08  289152·
 2013 09  299350·
 2013 10  899270.
 2013 11  909246.
 2013 12  969121·
 2014 01 49305·
 2014 02 149222.
 2014 03 388994.
 2014 04 239099·
 2014 05 49301·
 2014 06 789260·
 2014 07 99081.
 2014 08 529232.
 2014 09 69050·
 2014 10 899076·
 2014 11 429013.
 2014 12 539184.
 2015 01  109288·
 2015 02  789280.
 2015 03  989185·
 2015 04  199213·
 2015 05  419334.
 2015 06  19380·
 2015 07  679557.
 2015 08  699349·
 2015 09  509295·
 2015 10  409537.
 2015 11  609319·
 2015 12  489203·
 2016 01 119210·
 2016 02 19076.
 2016 03 159350·
 2016 04 259373.
 2016 05 279286·
 2016 06 179254.
 2016 07 979191·
 2016 08 949206·
 2016 09 219461.
 2016 10 449496.
 2016 11 919504·
 2016 12 759409·
 2017 01  449057.
 2017 02  649269·
 2017 03  129344.
 2017 04  109464·
 2017 05  729593·


 2017 06  829401·
 2017 07  979308·
 2017 08  708955·
 2017 09  59049.
 2017 10  329343·
 2017 11  99431.
 2017 12  499336·
 2018 01 689262.
 2018 02 699363·
 2018 03 369350.
 2018 04 659542·
 2018 05 139516.
 2018 06 769164·
 2018 07 919147.
 2018 08 639283.
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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: Persons At Work in Durable Goods Manufacturing Industries, Wage and Salary Workers: 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

Unemployment data for every county in the U.S..
Click for Illinois counties, then follow the example for your state

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