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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 9519598·
 2000 02 1219764·
 2000 03 7919700.
 2000 04 2619474.
 2000 05 419321·
 2000 06 6619540·
 2000 07 6919225.
 2000 08 9919240·
 2000 09 2218941.
 2000 10 6318872.
 2000 11 418950·
 2000 12 1519019·
 2001 01  118834.
 2001 02  8318826·
 2001 03  9618746.
 2001 04  1718505·
 2001 05  1618424·
 2001 06  3418239.
 2001 07  8417889·
 2001 08  7417631.
 2001 09  6717478·
 2001 10  4717449.
 2001 11  2917344·
 2001 12  8217507.
 2002 01 8017189·
 2002 02 7917262.
 2002 03 2117367·
 2002 04 5917045.
 2002 05 417036.
 2002 06 1116788.
 2002 07 7316742·
 2002 08 4816786·
 2002 09 1616497·
 2002 10 5116755·
 2002 11 2116734.
 2002 12 2016830·
 2003 01  1616925·
 2003 02  2917041.
 2003 03  2916722.
 2003 04  6916744·
 2003 05  3016509·
 2003 06  216380·
 2003 07  8516230·
 2003 08  1216500.
 2003 09  616243·
 2003 10  5216490·
 2003 11  116525.
 2003 12  9616536.
 2004 01 2216320·
 2004 02 8616260.
 2004 03 1716264.
 2004 04 8816225·
 2004 05 7716373.
 2004 06 3616222·
 2004 07 9316097.
 2004 08 8416251·
 2004 09 9716086·
 2004 10 5715814·
 2004 11 1915882.
 2004 12 116175.
 2005 01  3215917.
 2005 02  3215801·
 2005 03  715895.
 2005 04  8515918.
 2005 05  5815849·
 2005 06  6716124.
 2005 07  9515933.
 2005 08  415764·
 2005 09  7515882·
 2005 10  9315888·
 2005 11  4715910.
 2005 12  5216150·
 2006 01 816303·
 2006 02 6816180.
 2006 03 4916532.
 2006 04 5015970.
 2006 05 715944.
 2006 06 7416173.
 2006 07 1515967·
 2006 08 4016036.
 2006 09 4916082·
 2006 10 1616008·
 2006 11 8315631·
 2006 12 9215743.
 2007 01  3415578.
 2007 02  2615906·
 2007 03  1515926·
 2007 04  015794·
 2007 05  8615971.
 2007 06  6215725·
 2007 07  016072.
 2007 08  8315991·
 2007 09  5615996.
 2007 10  416148.
 2007 11  5016148·
 2007 12  8616125·
 2008 01 2115657.
 2008 02 5915669.
 2008 03 315759·
 2008 04 7715720.
 2008 05 7915651.
 2008 06 6015843·
 2008 07 2315873.
 2008 08 5115891.
 2008 09 5715647·
 2008 10 6215457·
 2008 11 9615252·
 2008 12 2614655.
 2009 01  414094·
 2009 02  4714124.
 2009 03  3713866·
 2009 04  4813950.
 2009 05  9714073·
 2009 06  2214055.
 2009 07  8214178·
 2009 08  8414071·
 2009 09  3514013·
 2009 10  1913691.
 2009 11  9513340·
 2009 12  3012995.
 2010 01 4512933·
 2010 02 9313232.
 2010 03 6413326.
 2010 04 413667.
 2010 05 7613867·
 2010 06 2813872.
 2010 07 114154.
 2010 08 5114020·
 2010 09 414025·
 2010 10 2914152.
 2010 11 4414011.
 2010 12 3914045·
 2011 01  2913876·
 2011 02  2813751·
 2011 03  5713769·
 2011 04  6314035·
 2011 05  7613779.
 2011 06  8214002.
 2011 07  2714051·
 2011 08  4214021.
 2011 09  9714365·
 2011 10  7214418·
 2011 11  6714263.
 2011 12  2014369.
 2012 01 6514050·
 2012 02 514124.
 2012 03 1514226·
 2012 04 6614301.
 2012 05 8314387·
 2012 06 1314423.
 2012 07 3314594.
 2012 08 7514405·
 2012 09 7514439.
 2012 10 5214656·
 2012 11 1114531·
 2012 12 6514322·
 2013 01  9114200·
 2013 02  414297.
 2013 03  6014323·
 2013 04  8114259·
 2013 05  714541.
 2013 06  7614575·
 2013 07  1914751.
 2013 08  9114869·
 2013 09  2414942·
 2013 10  9914682.
 2013 11  4914900·
 2013 12  9014742·
 2014 01 6614822·
 2014 02 2914676·
 2014 03 4114537.
 2014 04 9814618·
 2014 05 8514874·
 2014 06 4915168.
 2014 07 515001.
 2014 08 5715198·
 2014 09 5514875.
 2014 10 6614815.
 2014 11 8114546·
 2014 12 3814641·
 2015 01  7614873·
 2015 02  914802.
 2015 03  3014726.
 2015 04  3414767·
 2015 05  7514725.
 2015 06  3815041.
 2015 07  4115459.
 2015 08  6515420·
 2015 09  215316·
 2015 10  3215409.
 2015 11  2715034·
 2015 12  7514947·
 2016 01 3214934·
 2016 02 9914755·
 2016 03 2615152.
 2016 04 3215054.
 2016 05 6514949·
 2016 06 7115011.
 2016 07 015144.
 2016 08 3215141.
 2016 09 2715465.
 2016 10 315570·
 2016 11 3815273·
 2016 12 9315161.
 2017 01  6814720·
 2017 02  7815017·


 2017 03  5215132·
 2017 04  5915501·
 2017 05  6415429·
 2017 06  315281.
 2017 07  8015271.
 2017 08  9914697·
 2017 09  1514845·
 2017 10  815167.
 2017 11  8515339·
 2017 12  815050·
 2018 01 4714874.
 2018 02 5115129·
 2018 03 5515224.
 2018 04 515467·
 2018 05 915416.
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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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