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 Series Title: Men, employed government wage and salary workers in Construction: NSA
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 2000 01 65394·
 2000 02 38376.
 2000 03 88392·
 2000 04 73451·
 2000 05 77485·
 2000 06 85463·
 2000 07 84441.
 2000 08 92396.
 2000 09 5395·
 2000 10 81399·
 2000 11 32392·
 2000 12 59400·
 2001 01  0389.
 2001 02  6373.
 2001 03  43380·
 2001 04  20364.
 2001 05  38365.
 2001 06  69385.
 2001 07  56385.
 2001 08  42391·
 2001 09  17387·
 2001 10  99390·
 2001 11  34379·
 2001 12  20399·
 2002 01 65423.
 2002 02 55400.
 2002 03 64411·
 2002 04 74408.
 2002 05 31422.
 2002 06 18456.
 2002 07 59461·
 2002 08 47416.
 2002 09 90408·
 2002 10 93418.
 2002 11 58440.
 2002 12 8391.
 2003 01  44414.
 2003 02  14382.
 2003 03  23363.
 2003 04  53418·
 2003 05  17489.
 2003 06  36524.
 2003 07  42531.
 2003 08  98519·
 2003 09  60465·
 2003 10  42481.
 2003 11  27475.
 2003 12  90415·
 2004 01 48418·
 2004 02 37399.
 2004 03 18400.
 2004 04 97432·
 2004 05 82435·
 2004 06 54443.
 2004 07 76469·
 2004 08 13444·
 2004 09 86435.
 2004 10 49459·
 2004 11 90476·
 2004 12 58426·
 2005 01  13445.
 2005 02  4438.
 2005 03  73437.
 2005 04  75430.
 2005 05  36420·
 2005 06  26402.
 2005 07  62424.
 2005 08  33401·
 2005 09  56382·
 2005 10  45377·
 2005 11  20376·
 2005 12  28375·
 2006 01 99374·
 2006 02 19390·
 2006 03 35401.
 2006 04 77365·
 2006 05 15368.
 2006 06 30395·
 2006 07 20377.
 2006 08 25406.
 2006 09 79407.
 2006 10 83412·
 2006 11 13430.
 2006 12 42461.
 2007 01  92421.
 2007 02  11426·
 2007 03  77453·
 2007 04  21471·
 2007 05  79440·
 2007 06  71425·
 2007 07  0404·
 2007 08  81404.
 2007 09  90357.
 2007 10  43367.
 2007 11  94341·
 2007 12  67326.
 2008 01 2369·
 2008 02 35375.
 2008 03 98379.
 2008 04 48354.
 2008 05 14382.
 2008 06 78378.
 2008 07 74403.
 2008 08 17422·
 2008 09 51413.
 2008 10 29423.
 2008 11 11422.
 2008 12 95415·
 2009 01  65419.
 2009 02  69443.
 2009 03  21409·
 2009 04  25403.
 2009 05  30461·
 2009 06  6453.
 2009 07  42451·
 2009 08  76436.
 2009 09  47372.
 2009 10  70375·
 2009 11  36379·
 2009 12  43444·
 2010 01 42457·
 2010 02 19439.
 2010 03 93418.
 2010 04 44413·
 2010 05 64404.
 2010 06 34414.
 2010 07 24426.
 2010 08 24380.
 2010 09 89355.
 2010 10 21356.
 2010 11 68340.
 2010 12 52406·
 2011 01  17402.
 2011 02  13417·
 2011 03  88372·
 2011 04  21375.
 2011 05  75318·
 2011 06  65331·
 2011 07  70353·
 2011 08  53367·
 2011 09  11349.
 2011 10  61366·
 2011 11  30410.
 2011 12  89414·
 2012 01 3411.


 2012 02 5376.
 2012 03 3359.
 2012 04 0348·
 2012 05 49344.
 2012 06 31340·
 2012 07 54397.
 2012 08 79420·
 2012 09 76352·
 2012 10 94371·
 2012 11 69362.
 2012 12 46378·
 2013 01  33377.
 2013 02  76348·
 2013 03  62325·
 2013 04  45317·
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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 Construction: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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