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 Series Title: Employed: Wage and salary workers, Manufacturing: 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 5919598·
 2000 02 9919764.
 2000 03 4319700·
 2000 04 119474.
 2000 05 619321.
 2000 06 9319540.
 2000 07 019225.
 2000 08 9319240·
 2000 09 2018941·
 2000 10 8618872.
 2000 11 5718950·
 2000 12 8319019.
 2001 01  5018834.
 2001 02  6018826.
 2001 03  2918746·
 2001 04  1618505·
 2001 05  7218424·
 2001 06  2018239.
 2001 07  5217889·
 2001 08  6117631.
 2001 09  8717478·
 2001 10  9817449.
 2001 11  9017344.
 2001 12  1217507·
 2002 01 2017189.
 2002 02 5217262·
 2002 03 3017367.
 2002 04 8817045·
 2002 05 2117036.
 2002 06 6216788.
 2002 07 8616742.
 2002 08 3416786.
 2002 09 6516497·
 2002 10 3516755.
 2002 11 9516734.
 2002 12 1816830·
 2003 01  5416925.
 2003 02  417041·
 2003 03  2016722.
 2003 04  3516744.
 2003 05  1216509.
 2003 06  2316380·
 2003 07  4916230.
 2003 08  316500.
 2003 09  9016243.
 2003 10  7716490.
 2003 11  9416525.
 2003 12  6816536·
 2004 01 6416320.
 2004 02 7016260.
 2004 03 9516264·
 2004 04 9716225.
 2004 05 3316373.
 2004 06 3416222.
 2004 07 1416097·
 2004 08 8616251.
 2004 09 2316086·
 2004 10 2715814·
 2004 11 3815882.
 2004 12 5316175.
 2005 01  8415917·
 2005 02  3015801.
 2005 03  8015895·
 2005 04  4315918·
 2005 05  9215849·
 2005 06  4916124·
 2005 07  7915933.
 2005 08  2415764.
 2005 09  4715882·
 2005 10  1615888·
 2005 11  9715910.
 2005 12  9116150.
 2006 01 7516303·
 2006 02 8716180·
 2006 03 2316532.
 2006 04 6315970.
 2006 05 2615944.
 2006 06 4616173·
 2006 07 6815967.
 2006 08 8416036·
 2006 09 7616082·
 2006 10 9716008·
 2006 11 7215631.
 2006 12 2315743·
 2007 01  2415578·
 2007 02  7315906·
 2007 03  9615926.
 2007 04  7515794·
 2007 05  9615971·
 2007 06  3015725.
 2007 07  2916072.
 2007 08  5815991.
 2007 09  4315996·
 2007 10  5016148.
 2007 11  8316148.
 2007 12  1616125·
 2008 01 4015657·
 2008 02 3915669.
 2008 03 9715759.
 2008 04 2015720·
 2008 05 8715651.
 2008 06 3015843.
 2008 07 3415873.
 2008 08 6215891.
 2008 09 915647·
 2008 10 7815457.
 2008 11 8015252.
 2008 12 6214655.
 2009 01  5814094·
 2009 02  6714124.
 2009 03  5013866·
 2009 04  6513950·
 2009 05  914073·
 2009 06  114055·
 2009 07  8114178.
 2009 08  3914071·
 2009 09  6114013·
 2009 10  1313691·
 2009 11  3613340·
 2009 12  7812995·
 2010 01 4012933·
 2010 02 5913232·
 2010 03 313326·
 2010 04 213667.
 2010 05 9813867.
 2010 06 2113872·
 2010 07 9414154.
 2010 08 5414020·
 2010 09 814025.
 2010 10 714152·
 2010 11 4814011·
 2010 12 514045.
 2011 01  7213876.
 2011 02  4613751.
 2011 03  2813769.
 2011 04  4714035·
 2011 05  1413779.
 2011 06  9614002.
 2011 07  2114051·
 2011 08  114021·
 2011 09  8614365.
 2011 10  3914418·
 2011 11  4014263.
 2011 12  1014369.
 2012 01 6214050.
 2012 02 8214124·
 2012 03 2414226.
 2012 04 4314301·
 2012 05 4414387·
 2012 06 5514423·
 2012 07 3514594.
 2012 08 9514405.
 2012 09 5514439·
 2012 10 1514656·
 2012 11 6014531.
 2012 12 8514322.
 2013 01  4814200·
 2013 02  4514297.
 2013 03  1414323·
 2013 04  5714259.
 2013 05  9714541.
 2013 06  5114575.
 2013 07  3314751.
 2013 08  7914869·
 2013 09  214942·
 2013 10  6414682.
 2013 11  8114900.
 2013 12  4714742.
 2014 01 8914822.
 2014 02 4114676·
 2014 03 4514537.
 2014 04 7914618·
 2014 05 914874·
 2014 06 6415168·
 2014 07 3915001·
 2014 08 2015198.
 2014 09 3714875.
 2014 10 3914815.
 2014 11 014546.
 2014 12 3814641·
 2015 01  7214873·
 2015 02  9914802.
 2015 03  9114726.
 2015 04  2714767·
 2015 05  4114725·
 2015 06  9915041.
 2015 07  115459.
 2015 08  815420·
 2015 09  9415316·
 2015 10  2115409·
 2015 11  4115034.
 2015 12  2414947·
 2016 01 614934.
 2016 02 7214755.
 2016 03 5015152·
 2016 04 4315054·
 2016 05 7814949·
 2016 06 8415011·
 2016 07 9115144·
 2016 08 6115141.
 2016 09 3615465.
 2016 10 1315570·
 2016 11 5215273.
 2016 12 9715161.
 2017 01  2814720.
 2017 02  4115017·
 2017 03  4515132·
 2017 04  9415501·
 2017 05  3215429.
 2017 06  7415281.
 2017 07  915271.
 2017 08  2114697.


 2017 09  4614845.
 2017 10  4515167.
 2017 11  615339·
 2017 12  7415050·
 2018 01 9814874.
 2018 02 915129·
 2018 03 2415224·
 2018 04 7015467·
 2018 05 3615416.
 2018 06 4915220·
 2018 07 7715084·
 2018 08 5515030.
 2018 09 3715119.
 2018 10 7015582·
 2018 11 115725·
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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: Wage and salary workers, Manufacturing: 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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