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 Series Title: Employed: Wage and salary workers, Transportation and warehousing, Women: NSA
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 2000 01 161486.
 2000 02 411564·
 2000 03 701562.
 2000 04 861482·
 2000 05 981507.
 2000 06 151403.
 2000 07 501421.
 2000 08 451398·
 2000 09 221407·
 2000 10 631458.
 2000 11 61409·
 2000 12 771450.
 2001 01  381396·
 2001 02  651437.
 2001 03  501472·
 2001 04  271451·
 2001 05  211479.
 2001 06  301480.
 2001 07  221368·
 2001 08  631431·
 2001 09  711387.
 2001 10  871354.
 2001 11  821394.
 2001 12  811417·
 2002 01 141450.
 2002 02 951466·
 2002 03 211410.
 2002 04 991483.
 2002 05 11412·
 2002 06 341347.
 2002 07 491377.
 2002 08 621424·
 2002 09 61491·
 2002 10 121420·
 2002 11 61399.
 2002 12 381319.
 2003 01  301321·
 2003 02  601360·
 2003 03  541360.
 2003 04  211409·
 2003 05  991361·
 2003 06  341333.
 2003 07  811331·
 2003 08  321388.
 2003 09  631444.
 2003 10  171448·
 2003 11  01374.
 2003 12  131358.
 2004 01 971322·
 2004 02 141310.
 2004 03 491361·
 2004 04 341372.
 2004 05 11306.
 2004 06 581331.
 2004 07 911389.
 2004 08 901306.
 2004 09 21405·
 2004 10 51414.
 2004 11 131334.
 2004 12 991348·
 2005 01  481345.
 2005 02  371379·
 2005 03  281387·
 2005 04  51319.
 2005 05  171367·
 2005 06  601384·
 2005 07  751396.
 2005 08  781475.
 2005 09  81521·
 2005 10  61469.
 2005 11  171502·
 2005 12  121489·
 2006 01 471515.
 2006 02 321522.
 2006 03 401478·
 2006 04 261460·
 2006 05 831470.
 2006 06 201421.
 2006 07 581432.
 2006 08 631529.
 2006 09 931525·
 2006 10 751508·
 2006 11 101461·
 2006 12 941519.
 2007 01  771592.
 2007 02  301647.
 2007 03  571677·
 2007 04  131539.
 2007 05  601521.
 2007 06  421538.
 2007 07  881522·
 2007 08  381546·
 2007 09  921572·
 2007 10  911512·
 2007 11  161533.
 2007 12  131549·
 2008 01 491528.
 2008 02 851561·
 2008 03 781562·
 2008 04 81613·
 2008 05 321658.
 2008 06 551628·
 2008 07 371543.
 2008 08 171472.
 2008 09 651296.
 2008 10 581286·
 2008 11 821377·
 2008 12 591483·
 2009 01  991426.
 2009 02  751449·
 2009 03  251459.
 2009 04  791405.
 2009 05  101455·
 2009 06  141379·
 2009 07  41358·
 2009 08  441326·
 2009 09  981366.
 2009 10  51311.
 2009 11  821289.
 2009 12  501312.
 2010 01 881265·
 2010 02 61287·
 2010 03 471274.
 2010 04 161319.
 2010 05 311316.
 2010 06 971433·
 2010 07 111341.
 2010 08 851347·
 2010 09 21347·
 2010 10 871312.
 2010 11 131278·
 2010 12 281286·
 2011 01  11238.
 2011 02  51231.
 2011 03  161266·
 2011 04  371285·
 2011 05  541297·
 2011 06  101336.
 2011 07  71337.
 2011 08  321328.
 2011 09  111342·
 2011 10  821354·
 2011 11  991333.
 2011 12  581321.
 2012 01 481351·
 2012 02 291386.


 2012 03 311360.
 2012 04 831325·
 2012 05 651437·
 2012 06 811398·
 2012 07 651357·
 2012 08 21416.
 2012 09 881347·
 2012 10 961273·
 2012 11 881395.
 2012 12 341415·
 2013 01  661408·
 2013 02  551498.
 2013 03  151455·
 2013 04  221472·
 2013 05  751494·
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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: Employed: Wage and salary workers, Transportation and warehousing, Women: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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