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 Series Title: Total 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 4490·
 2012 03 3994·
 2012 02 94105.
 2012 01 25116.
 2011 12  69126·
 2011 11  70106.
 2011 10  70106·
 2011 09  4393·
 2011 08  4291.
 2011 07  8088·
 2011 06  2874.
 2011 05  4192.
 2011 04  1387.
 2011 03  5290·
 2011 02  81108.
 2011 01  63105·
 2010 12 57107·
 2010 11 92117.
 2010 10 66124·
 2010 09 78117·
 2010 08 76102.
 2010 07 32110·
 2010 06 4893·
 2010 05 8171.
 2010 04 9393.
 2010 03 27106·
 2010 02 13108.
 2010 01 90115.
 2009 12  59117.
 2009 11  61136.
 2009 10  75130·
 2009 09  50130.
 2009 08  51110·
 2009 07  39122·
 2009 06  72133·
 2009 05  30104·
 2009 04  6872·
 2009 03  9489·
 2009 02  66114·
 2009 01  23108·
 2008 12 36115.
 2008 11 81113.
 2008 10 45107·
 2008 09 50123.
 2008 08 4126.
 2008 07 83137.
 2008 06 22131·
 2008 05 5383·
 2008 04 50103.
 2008 03 598·
 2008 02 35106·
 2008 01 3125.
 2007 12  72112·
 2007 11  81103.
 2007 10  48107.
 2007 09  9485.
 2007 08  9684·
 2007 07  6698.
 2007 06  4786.
 2007 05  4486·
 2007 04  73116.
 2007 03  42109·
 2007 02  4698·
 2007 01  9793.
 2006 12 7977·
 2006 11 1687·
 2006 10 8293.
 2006 09 2472·
 2006 08 1272·
 2006 07 1966·
 2006 06 1968·
 2006 05 1872.
 2006 04 088·
 2006 03 886·
 2006 02 4579.
 2006 01 9899·
 2005 12  91106·
 2005 11  65108·
 2005 10  7294·
 2005 09  871.
 2005 08  6369.
 2005 07  9688·
 2005 06  3882·
 2005 05  1787.
 2005 04  1476.
 2005 03  3264·
 2005 02  656·
 2005 01  2158.
 2004 12 7163.
 2004 11 3261·
 2004 10 6472·
 2004 09 3669·
 2004 08 8368.
 2004 07 7558.
 2004 06 2464·
 2004 05 968·
 2004 04 2765·
 2004 03 7055.
 2004 02 2647.
 2004 01 853.
 2003 12  255.
 2003 11  4677·
 2003 10  3183.
 2003 09  2786·
 2003 08  3468·
 2003 07  6280·
 2003 06  2857·
 2003 05  8563·
 2003 04  7472.
 2003 03  9951·
 2003 02  2956·
 2003 01  2780.
 2002 12 9677·
 2002 11 6380.
 2002 10 7385.
 2002 09 2166.
 2002 08 286.
 2002 07 8672.
 2002 06 2268.
 2002 05 6268.
 2002 04 1656·
 2002 03 2562.
 2002 02 6356.
 2002 01 6957.
 2001 12  8959·
 2001 11  6050·
 2001 10  1171·
 2001 09  86111.
 2001 08  96159·
 2001 07  077.
 2001 06  377·
 2001 05  8157·
 2001 04  3851·
 2001 03  7665.
 2001 02  174.
 2001 01  5196·
 2000 12 4090.
 2000 11 4384.
 2000 10 9563·
 2000 09 1268·
 2000 08 5260.
 2000 07 8558·
 2000 06 9569.
 2000 05 1074.
 2000 04 5163·
 2000 03 729.
 2000 02 4164·
 2000 01 1445.
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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: Total 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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