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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 4319598.
 2000 02 9319764·
 2000 03 2619700.
 2000 04 519474·
 2000 05 2119321·
 2000 06 6419540·
 2000 07 2919225.
 2000 08 3819240·
 2000 09 9618941.
 2000 10 6418872·
 2000 11 6418950·
 2000 12 119019.
 2001 01  1918834·
 2001 02  7618826·
 2001 03  4418746.
 2001 04  3818505.
 2001 05  6618424.
 2001 06  618239.
 2001 07  717889·
 2001 08  1817631.
 2001 09  3617478·
 2001 10  8517449.
 2001 11  1617344·
 2001 12  3617507.
 2002 01 5617189.
 2002 02 7017262.
 2002 03 5917367.
 2002 04 1017045·
 2002 05 7517036·
 2002 06 4416788·
 2002 07 4816742·
 2002 08 8416786.
 2002 09 6916497.
 2002 10 1216755.
 2002 11 2216734·
 2002 12 2916830.
 2003 01  3816925·
 2003 02  617041.
 2003 03  4316722·
 2003 04  3716744·
 2003 05  816509.
 2003 06  8316380.
 2003 07  9916230·
 2003 08  2816500.
 2003 09  2916243·
 2003 10  2516490.
 2003 11  416525.
 2003 12  4716536·
 2004 01 7716320.
 2004 02 3816260.
 2004 03 9516264.
 2004 04 6216225.
 2004 05 5116373.
 2004 06 5316222.
 2004 07 3416097·
 2004 08 6716251.
 2004 09 7816086·
 2004 10 2815814·
 2004 11 1115882.
 2004 12 8216175.
 2005 01  715917.
 2005 02  4415801.
 2005 03  3715895·
 2005 04  5015918·
 2005 05  1515849.
 2005 06  716124·
 2005 07  5115933.
 2005 08  4215764·
 2005 09  115882.
 2005 10  5015888.
 2005 11  1515910·
 2005 12  5016150·
 2006 01 9116303.
 2006 02 2916180·
 2006 03 1816532·
 2006 04 9515970.
 2006 05 3515944·
 2006 06 2616173·
 2006 07 7215967·
 2006 08 2016036.
 2006 09 816082.
 2006 10 4716008.
 2006 11 1615631·
 2006 12 9515743·
 2007 01  1215578·
 2007 02  2315906.
 2007 03  1115926·
 2007 04  1315794·
 2007 05  7115971·
 2007 06  1215725.
 2007 07  4616072·
 2007 08  9315991.
 2007 09  3615996·
 2007 10  9616148.
 2007 11  3516148·
 2007 12  8116125·
 2008 01 8215657·
 2008 02 8015669.
 2008 03 1415759.
 2008 04 4515720.
 2008 05 1015651·
 2008 06 9715843.
 2008 07 4615873.
 2008 08 7815891·
 2008 09 4415647·
 2008 10 215457·
 2008 11 2015252·
 2008 12 114655.
 2009 01  3614094·
 2009 02  7914124.
 2009 03  4913866·
 2009 04  5813950·
 2009 05  6114073·
 2009 06  3314055·
 2009 07  7014178·
 2009 08  1714071·
 2009 09  1914013.
 2009 10  9513691.
 2009 11  4613340.
 2009 12  7312995.
 2010 01 3512933·
 2010 02 2413232·
 2010 03 6513326.
 2010 04 4413667.
 2010 05 6013867.
 2010 06 013872.
 2010 07 4014154·
 2010 08 7614020·
 2010 09 7014025·
 2010 10 2914152.
 2010 11 914011.
 2010 12 3714045·
 2011 01  6413876.
 2011 02  4513751·
 2011 03  3513769.
 2011 04  2114035.
 2011 05  6813779·
 2011 06  214002.
 2011 07  614051.
 2011 08  4714021·
 2011 09  3314365.
 2011 10  8414418.
 2011 11  3414263.
 2011 12  6014369·
 2012 01 3414050.
 2012 02 9614124·
 2012 03 5714226.
 2012 04 2914301.
 2012 05 7114387.
 2012 06 7014423.
 2012 07 3914594.
 2012 08 4714405·
 2012 09 7014439.
 2012 10 6214656.
 2012 11 6714531.
 2012 12 3514322.
 2013 01  8014200·
 2013 02  5614297·
 2013 03  5414323·
 2013 04  3514259.
 2013 05  7814541·
 2013 06  5614575.
 2013 07  3814751·
 2013 08  1814869.
 2013 09  6414942·
 2013 10  9514682·
 2013 11  8214900·
 2013 12  7814742·
 2014 01 6314822.
 2014 02 2914676.
 2014 03 7414537·
 2014 04 3214618·
 2014 05 2614874·
 2014 06 4015168·
 2014 07 2615001·
 2014 08 2715198·
 2014 09 2814875·
 2014 10 3514815·
 2014 11 7814546.
 2014 12 3014641.
 2015 01  6914873.
 2015 02  4614802.
 2015 03  9014726·
 2015 04  3614767·
 2015 05  7514725·
 2015 06  2815041.
 2015 07  5215459.
 2015 08  6515420·
 2015 09  9615316.
 2015 10  6315409·
 2015 11  7615034·
 2015 12  5914947.
 2016 01 714934·
 2016 02 5914755.
 2016 03 015152·
 2016 04 8915054·
 2016 05 1014949·
 2016 06 4715011·
 2016 07 8715144·
 2016 08 4915141.
 2016 09 2915465·
 2016 10 8315570·
 2016 11 2615273·
 2016 12 5715161.
 2017 01  1514720.
 2017 02  4915017·
 2017 03  2815132·
 2017 04  5815501.
 2017 05  4215429.


 2017 06  5215281·
 2017 07  3115271.
 2017 08  2114697.
 2017 09  1314845·
 2017 10  2415167.
 2017 11  9915339·
 2017 12  4015050.
 2018 01 5114874·
 2018 02 2015129.
 2018 03 2015224·
 2018 04 3415467·
 2018 05 715416·
 2018 06 2315220·
 2018 07 615084·
 2018 08 4815030·
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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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