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 Series Title: Men, employed government wage and salary workers in Manufacturing: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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 2012 04 8361.
 2012 03 9769·
 2012 02 983.
 2012 01 193·
 2011 12  8393.
 2011 11  6369·
 2011 10  5675.
 2011 09  263·
 2011 08  2469·
 2011 07  361.
 2011 06  7954.
 2011 05  7672·
 2011 04  5768.
 2011 03  9880.
 2011 02  9095.
 2011 01  6886.
 2010 12 5780·
 2010 11 5483·
 2010 10 2991·
 2010 09 4790·
 2010 08 2480·
 2010 07 481.
 2010 06 5771·
 2010 05 755·
 2010 04 8569·
 2010 03 494.
 2010 02 6287.
 2010 01 67103.
 2009 12  88107·
 2009 11  36116·
 2009 10  58102.
 2009 09  72104·
 2009 08  1190.
 2009 07  694·
 2009 06  82101.
 2009 05  9080.
 2009 04  5260·
 2009 03  4668.
 2009 02  9791.
 2009 01  1577.
 2008 12 3883·
 2008 11 1285.
 2008 10 9279.
 2008 09 68103·
 2008 08 19104·
 2008 07 87118·
 2008 06 78106.
 2008 05 9169.
 2008 04 7093·
 2008 03 7674·
 2008 02 9473.
 2008 01 5593·
 2007 12  9273·
 2007 11  1273.
 2007 10  379·
 2007 09  5355.
 2007 08  1061·
 2007 07  5282.
 2007 06  9271·
 2007 05  479·
 2007 04  74104.
 2007 03  7688·
 2007 02  7575.
 2007 01  5361.
 2006 12 6057.
 2006 11 9164.
 2006 10 8967·
 2006 09 6852·
 2006 08 6848.
 2006 07 3056.
 2006 06 9742·
 2006 05 4449.
 2006 04 2372·
 2006 03 4866·
 2006 02 8861.
 2006 01 077·
 2005 12  7785.
 2005 11  2789.
 2005 10  7383.
 2005 09  8052.
 2005 08  452·
 2005 07  7574.
 2005 06  9255·
 2005 05  5353·
 2005 04  547·
 2005 03  2239·
 2005 02  636·
 2005 01  1339.
 2004 12 550.
 2004 11 2646·
 2004 10 555.
 2004 09 8056·
 2004 08 5556·
 2004 07 6748.
 2004 06 9948·
 2004 05 9847.
 2004 04 2942·
 2004 03 5341.
 2004 02 2934·
 2004 01 3536.
 2003 12  2939.
 2003 11  1655·
 2003 10  5559.
 2003 09  8764.
 2003 08  7947·
 2003 07  1156.
 2003 06  6729·
 2003 05  7139·
 2003 04  3130.
 2003 03  2025·
 2003 02  7736.
 2003 01  3250.
 2002 12 5946.
 2002 11 5161.
 2002 10 2355.
 2002 09 4050.
 2002 08 6462.
 2002 07 3441·
 2002 06 6936·
 2002 05 8841.
 2002 04 7134·
 2002 03 2733·
 2002 02 134.
 2002 01 9637.
 2001 12  3141·
 2001 11  1132·
 2001 10  3253·
 2001 09  876.
 2001 08  1997·
 2001 07  9354·
 2001 06  254.
 2001 05  9241.
 2001 04  3636·
 2001 03  438.
 2001 02  7243·
 2001 01  4460·
 2000 12 658.
 2000 11 051·
 2000 10 3046·
 2000 09 8145.
 2000 08 8048·
 2000 07 6543·
 2000 06 8951.
 2000 05 4950·
 2000 04 3448·
 2000 03 425.
 2000 02 8847.
 2000 01 1732.
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US Unemployment Rate: Alternative Measures of Labor Underutilization

Charts

Unemployment Rate: US Unemployment Rate: 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: Men, employed government wage and salary workers in 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

Make charts for Okun's Law and Phillip's Curve

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