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 Series Title: Unemployment Level: Veterans, Gulf War Era, 35 to 44 years, Women: NSA
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 2006 05 866.
 2006 06 09.
 2006 07 204.
 2006 08 440·
 2006 09 938·
 2006 10 8811.
 2006 11 5511.
 2006 12 484.
 2007 01  3
 2007 02  124.
 2007 03  282.
 2007 04  882·
 2007 05  671·
 2007 06  549·
 2007 07  52
 2007 08  81·
 2007 09  610.
 2007 10  202·
 2007 11  6613.
 2007 12  7812·
 2008 01 856.
 2008 02 421.
 2008 03 320.
 2008 04 911·
 2008 05 654.
 2008 06 77
 2008 07 378.
 2008 08 6826.
 2008 09 5011.
 2008 10 527·
 2008 11 9610.
 2008 12 5015·
 2009 01  1610·
 2009 02  3515·
 2009 03  4524.
 2009 04  925.
 2009 05  6414.
 2009 06  9713.
 2009 07  489.
 2009 08  393·
 2009 09  1914.
 2009 10  4815.
 2009 11  9317.
 2009 12  5712.
 2010 01 3116.
 2010 02 6913·
 2010 03 9113·
 2010 04 926·
 2010 05 7624·
 2010 06 6930.
 2010 07 8310·
 2010 08 6311·
 2010 09 5412.
 2010 10 7718·
 2010 11 2913·
 2010 12 143.
 2011 01  9115.
 2011 02  5015.
 2011 03  1915·
 2011 04  8123·
 2011 05  3625·
 2011 06  7219.
 2011 07  6438.
 2011 08  813.
 2011 09  6625.
 2011 10  4719·
 2011 11  37·
 2011 12  648·
 2012 01 8129·
 2012 02 714·
 2012 03 016.
 2012 04 436·
 2012 05 614·
 2012 06 1018·
 2012 07 4020·
 2012 08 6517·
 2012 09 9123.
 2012 10 3716·
 2012 11 39
 2012 12 7313.
 2013 01  1229.
 2013 02  9416.
 2013 03  3220·
 2013 04  3718·
 2013 05  6945·
 2013 06  1328·
 2013 07  8527.
 2013 08  5120.
 2013 09  883·
 2013 10  5113·
 2013 11  8311.
 2013 12  3410·
 2014 01 1912·
 2014 02 9031.
 2014 03 4027.
 2014 04 3027·
 2014 05 3734·
 2014 06 3641.
 2014 07 9528.
 2014 08 821·
 2014 09 4342.
 2014 10 2035.
 2014 11 923·
 2014 12 6325.
 2015 01  6322.
 2015 02  9923·
 2015 03  718.
 2015 04  1319.
 2015 05  4629·
 2015 06  5621·
 2015 07  9422.
 2015 08  318.
 2015 09  6819.
 2015 10  9620·
 2015 11  1516.
 2015 12  110·
 2016 01 2917·
 2016 02 5210·
 2016 03 9818·
 2016 04 317.
 2016 05 5613·
 2016 06 7920.
 2016 07 3029.
 2016 08 2723.
 2016 09 9712.
 2016 10 604.
 2016 11 2512.
 2016 12 16
 2017 01  291.
 2017 02  125.
 2017 03  1919·
 2017 04  423.
 2017 05  526.
 2017 06  3411.
 2017 07  770·
 2017 08  9720·
 2017 09  91


 2017 10  165·
 2017 11  8510.
 2017 12  010·
 2018 01 9712·
 2018 02 2715.
 2018 03 587.
 2018 04 9610·
 2018 05 457·
 2018 06 76
 2018 07 3211·
 2018 08 5511·
 2018 09 3613.
 2018 10 92
 2018 11 705·
 2018 12 69
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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: Unemployment Level: Veterans, Gulf War Era, 35 to 44 years, Women: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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