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 Series Title: Employed: Leisure and hospitality, Asian: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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 2012 04 44890.
 2012 03 10829.
 2012 02 88836·
 2012 01 81878.
 2011 12  16812·
 2011 11  22817·
 2011 10  29765·
 2011 09  99803.
 2011 08  73789·
 2011 07  51847·
 2011 06  90880.
 2011 05  34882·
 2011 04  66822.
 2011 03  78786·
 2011 02  83783·
 2011 01  31761.
 2010 12 69783·
 2010 11 12757.
 2010 10 47826.
 2010 09 59818.
 2010 08 84851.
 2010 07 82825.
 2010 06 44803·
 2010 05 11803·
 2010 04 35810·
 2010 03 47799.
 2010 02 62746·
 2010 01 8756·
 2009 12  73786.
 2009 11  86740·
 2009 10  14787·
 2009 09  92754·
 2009 08  74768.
 2009 07  8862·
 2009 06  39879·
 2009 05  34814.
 2009 04  38822.
 2009 03  43835·
 2009 02  98791·
 2009 01  28780.
 2008 12 90816·
 2008 11 49762·
 2008 10 80804.
 2008 09 91809·
 2008 08 80775·
 2008 07 7762·
 2008 06 98771.
 2008 05 70754.
 2008 04 85763.
 2008 03 23809·
 2008 02 89802.
 2008 01 32857.
 2007 12  4812·
 2007 11  30755·
 2007 10  17837·
 2007 09  72798·
 2007 08  62760.
 2007 07  84808·
 2007 06  69714.
 2007 05  10680.
 2007 04  11656.
 2007 03  66702·
 2007 02  58660.
 2007 01  88648·
 2006 12 25659.
 2006 11 83681.
 2006 10 23743.
 2006 09 77753·
 2006 08 6679.
 2006 07 67752·
 2006 06 25722.
 2006 05 71764.
 2006 04 77788.
 2006 03 75700·
 2006 02 53647·
 2006 01 88651·
 2005 12  91653.
 2005 11  88660.
 2005 10  21744.
 2005 09  73686.
 2005 08  21707.
 2005 07  12760.
 2005 06  65697.
 2005 05  95750.
 2005 04  69668·
 2005 03  80673.
 2005 02  48729.
 2005 01  48682.
 2004 12 60701·
 2004 11 48674·
 2004 10 59705.
 2004 09 51613.
 2004 08 44702.
 2004 07 98738·
 2004 06 10690·
 2004 05 49761·
 2004 04 97779·
 2004 03 35745·
 2004 02 40680·
 2004 01 10659·
 2003 12  19649·
 2003 11  93637.
 2003 10  10706.
 2003 09  28638·
 2003 08  35652.
 2003 07  28615·
 2003 06  10663.
 2003 05  24717·
 2003 04  97666·
 2003 03  20707·
 2003 02  52655.
 2003 01  40668·
 2002 12 78735·
 2002 11 78776·
 2002 10 73757·
 2002 09 47723.
 2002 08 80645.
 2002 07 32683.
 2002 06 38674·
 2002 05 38617·
 2002 04 29707.
 2002 03 39725.
 2002 02 32748.
 2002 01 32765·
 2001 12  73814·
 2001 11  81783.
 2001 10  71731.
 2001 09  73682.
 2001 08  90638·
 2001 07  65675.
 2001 06  90617.
 2001 05  31650.
 2001 04  78654·
 2001 03  21671·
 2001 02  54705·
 2001 01  0720·
 2000 12 64718·
 2000 11 7658·
 2000 10 50585.
 2000 09 99586.
 2000 08 98606·
 2000 07 5648.
 2000 06 91696·
 2000 05 72711·
 2000 04 56726·
 2000 03 20739.
 2000 02 15697·
 2000 01 88676.
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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: Leisure and hospitality, Asian: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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