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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 412222·
 2000 02 3312192.
 2000 03 5112312·
 2000 04 5412345.
 2000 05 6212118·
 2000 06 9811911.
 2000 07 8711283.
 2000 08 8411535.
 2000 09 2411684·
 2000 10 9911822.
 2000 11 6211789·
 2000 12 5111936.
 2001 01  4011684.
 2001 02  1711677·
 2001 03  8811688·
 2001 04  9811466·
 2001 05  8511511·
 2001 06  6011209·
 2001 07  310605.
 2001 08  9410697·
 2001 09  6110783·
 2001 10  5910862.
 2001 11  7110597·
 2001 12  3410777.
 2002 01 9210534·
 2002 02 7010548.
 2002 03 7810622·
 2002 04 3610473.
 2002 05 2810406.
 2002 06 7510151.
 2002 07 389858.
 2002 08 4610111.
 2002 09 4610130·
 2002 10 8110477.
 2002 11 8910364·
 2002 12 3110447.
 2003 01  4610475.
 2003 02  1910434·
 2003 03  9310095·
 2003 04  8710020.
 2003 05  529981·
 2003 06  479931.
 2003 07  399291.
 2003 08  329809·
 2003 09  169810·
 2003 10  459948.
 2003 11  4010193.
 2003 12  1010201·
 2004 01 139982.
 2004 02 219971.
 2004 03 329678.
 2004 04 919827.
 2004 05 429825.
 2004 06 69681·
 2004 07 809499·
 2004 08 699886.
 2004 09 309940.
 2004 10 569806.
 2004 11 719889.
 2004 12 6210076.
 2005 01  2810015·
 2005 02  549805.
 2005 03  189887·
 2005 04  169912.
 2005 05  99745·
 2005 06  59863.
 2005 07  599392.
 2005 08  999461·
 2005 09  759828.
 2005 10  439920.
 2005 11  5710052.
 2005 12  410302.
 2006 01 5110307·
 2006 02 2210256.
 2006 03 9910403·
 2006 04 5310130·
 2006 05 8810034.
 2006 06 2510102.
 2006 07 999752·
 2006 08 889705.
 2006 09 619921.
 2006 10 599950·
 2006 11 959710·
 2006 12 789943·
 2007 01  699661.
 2007 02  5510005.
 2007 03  489941·
 2007 04  199853·
 2007 05  4010115.
 2007 06  699717·
 2007 07  489519·
 2007 08  289649·
 2007 09  229809.
 2007 10  859967·
 2007 11  710146·
 2007 12  5010105.
 2008 01 929892.
 2008 02 79820.
 2008 03 639867·
 2008 04 559967·
 2008 05 509790.
 2008 06 6810044.
 2008 07 799617·
 2008 08 369806·
 2008 09 219880·
 2008 10 249770·
 2008 11 439840·
 2008 12 139528.
 2009 01  569073.
 2009 02  578978·
 2009 03  678588·
 2009 04  298554.
 2009 05  298593·
 2009 06  748342·
 2009 07  908375.
 2009 08  558463.
 2009 09  428377·
 2009 10  68445·
 2009 11  758305·
 2009 12  838028·
 2010 01 207984·
 2010 02 108048.
 2010 03 88112·
 2010 04 338336·
 2010 05 138518.
 2010 06 678517·
 2010 07 48625.
 2010 08 498597·
 2010 09 978629.
 2010 10 858550·
 2010 11 08524.
 2010 12 18568.
 2011 01  718591·
 2011 02  958390·
 2011 03  608580.
 2011 04  838632.
 2011 05  628526.
 2011 06  538733·
 2011 07  708477.
 2011 08  138519·
 2011 09  198859·
 2011 10  418697·
 2011 11  438631.
 2011 12  358940.
 2012 01 198709·
 2012 02 668837.
 2012 03 198685.
 2012 04 208779.
 2012 05 618759.
 2012 06 598899·
 2012 07 598846·
 2012 08 618804·
 2012 09 719037.
 2012 10 779074.
 2012 11 529073·
 2012 12 778862·
 2013 01  998808·
 2013 02  28833.
 2013 03  108839·
 2013 04  138789.
 2013 05  228746·
 2013 06  408890·
 2013 07  718930·
 2013 08  379152·
 2013 09  389350·
 2013 10  249270·
 2013 11  989246·
 2013 12  439121·
 2014 01 739305·
 2014 02 89222.
 2014 03 798994·
 2014 04 529099.
 2014 05 799301·
 2014 06 769260.
 2014 07 289081·
 2014 08 69232.
 2014 09 299050·
 2014 10 349076.
 2014 11 819013·
 2014 12 769184·
 2015 01  259288·
 2015 02  149280·
 2015 03  29185·
 2015 04  549213.
 2015 05  939334.
 2015 06  719380.
 2015 07  789557·
 2015 08  619349·
 2015 09  829295.
 2015 10  899537.
 2015 11  239319.
 2015 12  419203·
 2016 01 679210.
 2016 02 739076·
 2016 03 749350.
 2016 04 629373.
 2016 05 509286.
 2016 06 559254·
 2016 07 959191.
 2016 08 199206.
 2016 09 559461.
 2016 10 919496·
 2016 11 729504·
 2016 12 309409·
 2017 01  339057·
 2017 02  649269.
 2017 03  209344.
 2017 04  419464.
 2017 05  609593·
 2017 06  809401·
 2017 07  769308.
 2017 08  208955.


 2017 09  369049.
 2017 10  719343.
 2017 11  29431.
 2017 12  629336·
 2018 01 859262·
 2018 02 939363·
 2018 03 889350·
 2018 04 849542·
 2018 05 599516.
 2018 06 279164·
 2018 07 459147.
 2018 08 339283·
 2018 09 339456·
 2018 10 829917·
 2018 11 119800.
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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

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