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 Series Title: Employed: Hospitals, Asian: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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 2012 04 43382·
 2012 03 74404·
 2012 02 20395·
 2012 01 34477.
 2011 12  94415.
 2011 11  77466.
 2011 10  65454.
 2011 09  69468·
 2011 08  80443.
 2011 07  47421.
 2011 06  80458·
 2011 05  71450.
 2011 04  51432·
 2011 03  67497·
 2011 02  77462.
 2011 01  84489.
 2010 12 84465.
 2010 11 41451·
 2010 10 94438.
 2010 09 78401·
 2010 08 77468.
 2010 07 3444.
 2010 06 95482·
 2010 05 47464.
 2010 04 57448·
 2010 03 9426·
 2010 02 67431.
 2010 01 10442·
 2009 12  75496.
 2009 11  40474·
 2009 10  24463.
 2009 09  11420·
 2009 08  4412·
 2009 07  3412·
 2009 06  2385·
 2009 05  19405.
 2009 04  47421·
 2009 03  30410·
 2009 02  65437·
 2009 01  29475·
 2008 12 28470·
 2008 11 77524.
 2008 10 1546.
 2008 09 59498·
 2008 08 97499.
 2008 07 27470·
 2008 06 23377.
 2008 05 54400·
 2008 04 31364.
 2008 03 84387·
 2008 02 68400.
 2008 01 82448.
 2007 12  28471.
 2007 11  82490·
 2007 10  0447.
 2007 09  39437·
 2007 08  16467·
 2007 07  77440·
 2007 06  6405.
 2007 05  43379·
 2007 04  43374.
 2007 03  51372.
 2007 02  99401·
 2007 01  38445.
 2006 12 87367.
 2006 11 10428.
 2006 10 17366.
 2006 09 93394·
 2006 08 46420.
 2006 07 85399.
 2006 06 24489·
 2006 05 3420·
 2006 04 46396·
 2006 03 34334·
 2006 02 6370.
 2006 01 87389·
 2005 12  39396·
 2005 11  38427·
 2005 10  77382·
 2005 09  88379.
 2005 08  98424·
 2005 07  4435·
 2005 06  75427·
 2005 05  76428·
 2005 04  25410.
 2005 03  64339·
 2005 02  62301.
 2005 01  46326·
 2004 12 45333·
 2004 11 73383.
 2004 10 27432.
 2004 09 15382.
 2004 08 8371.
 2004 07 14380.
 2004 06 82387·
 2004 05 29389·
 2004 04 90385.
 2004 03 93348.
 2004 02 66293.
 2004 01 57273.
 2003 12  91251.
 2003 11  42289.
 2003 10  40363·
 2003 09  92382.
 2003 08  36428.
 2003 07  18397.
 2003 06  94366.
 2003 05  54329.
 2003 04  76331·
 2003 03  2305·
 2003 02  39328·
 2003 01  87289.
 2002 12 87378·
 2002 11 1369·
 2002 10 15340·
 2002 09 60361.
 2002 08 68339.
 2002 07 47359.
 2002 06 83340·
 2002 05 67303.
 2002 04 45332·
 2002 03 95336.
 2002 02 32372.
 2002 01 27361.
 2001 12  68318.
 2001 11  29323·
 2001 10  74292·
 2001 09  85329·
 2001 08  13340·
 2001 07  54371.
 2001 06  47332·
 2001 05  10319.
 2001 04  81323.
 2001 03  1282.
 2001 02  15300·
 2001 01  95320·
 2000 12 96298.
 2000 11 29330·
 2000 10 65315·
 2000 09 61339·
 2000 08 9347.
 2000 07 18379·
 2000 06 10368·
 2000 05 50366.
 2000 04 96324.
 2000 03 75302·
 2000 02 88309.
 2000 01 32324.
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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: Hospitals, Asian: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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