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 Series Title: Population Level: 55-64 years, Hispanic or Latino Women: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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 2012 04 891867.
 2012 03 471859·
 2012 02 491852.
 2012 01 601843·
 2011 12  701746·
 2011 11  701735·
 2011 10  551729·
 2011 09  461723.
 2011 08  481718·
 2011 07  241710.
 2011 06  931707·
 2011 05  621701·
 2011 04  751690·
 2011 03  891684.
 2011 02  761676.
 2011 01  521665.
 2010 12 251667·
 2010 11 711659.
 2010 10 421651.
 2010 09 851644.
 2010 08 981636.
 2010 07 41629·
 2010 06 551624.
 2010 05 561620·
 2010 04 211613.
 2010 03 431607.
 2010 02 01599.
 2010 01 831592.
 2009 12  431603.
 2009 11  691592·
 2009 10  931584·
 2009 09  111577·
 2009 08  401569·
 2009 07  901560·
 2009 06  701556·
 2009 05  91546·
 2009 04  121536·
 2009 03  381530·
 2009 02  941522·
 2009 01  701517.
 2008 12 861515·
 2008 11 681505·
 2008 10 541497·
 2008 09 141493·
 2008 08 101483.
 2008 07 631479·
 2008 06 611471.
 2008 05 861466.
 2008 04 611456.
 2008 03 281450·
 2008 02 551444.
 2008 01 541438.
 2007 12  381437.
 2007 11  971430.
 2007 10  981425.
 2007 09  121417·
 2007 08  681410·
 2007 07  251399·
 2007 06  781393.
 2007 05  801387·
 2007 04  11380.
 2007 03  941374.
 2007 02  71367·
 2007 01  21358·
 2006 12 111347·
 2006 11 111341.
 2006 10 241333·
 2006 09 471327.
 2006 08 01322·
 2006 07 71316.
 2006 06 911311.
 2006 05 81304·
 2006 04 931297.
 2006 03 391290.
 2006 02 971283·
 2006 01 61278·
 2005 12  401272.
 2005 11  891267·
 2005 10  551258.
 2005 09  841256·
 2005 08  171250·
 2005 07  621242.
 2005 06  11234·
 2005 05  121227.
 2005 04  241220·
 2005 03  921214.
 2005 02  01208·
 2005 01  831199.
 2004 12 861196.
 2004 11 351193·
 2004 10 381185.
 2004 09 171178·
 2004 08 541172·
 2004 07 711164.
 2004 06 291160.
 2004 05 581152.
 2004 04 31143·
 2004 03 81139·
 2004 02 111132.
 2004 01 741127.
 2003 12  341138.
 2003 11  781135.
 2003 10  471131·
 2003 09  611123·
 2003 08  721116·
 2003 07  371107·
 2003 06  241100·
 2003 05  381093·
 2003 04  671087.
 2003 03  671081·
 2003 02  561077.
 2003 01  471072.
 2002 12 951100.
 2002 11 731093.
 2002 10 801069.
 2002 09 591077.
 2002 08 561074.
 2002 07 891064·
 2002 06 591047.
 2002 05 681035·
 2002 04 751039.
 2002 03 711006.
 2002 02 82999·
 2002 01 931011.
 2001 12  31027.
 2001 11  01040·
 2001 10  601051.
 2001 09  781045.
 2001 08  161019·
 2001 07  83999.
 2001 06  32936·
 2001 05  92895·
 2001 04  14874.
 2001 03  51904·
 2001 02  61911.
 2001 01  29911·
 2000 12 21944.
 2000 11 62967.
 2000 10 35993·
 2000 09 81021.
 2000 08 89989.
 2000 07 96957·
 2000 06 66911.
 2000 05 74904.
 2000 04 93924·
 2000 03 61908.
 2000 02 92877.
 2000 01 96845.
 1999 12  33902.
 1999 11  89913.
 1999 10  77935·
 1999 09  68979·
 1999 08  35937.
 1999 07  34954·
 1999 06  9974.
 1999 05  9944·
 1999 04  481029·
 1999 03  811026·
 1999 02  99919·
 1999 01  62850·
 1998 12 50806·
 1998 11 34815·
 1998 10 86853.
 1998 09 98862·
 1998 08 39841·
 1998 07 26806.
 1998 06 33841·
 1998 05 11857.
 1998 04 41914·
 1998 03 14888·
 1998 02 28840.
 1998 01 19805.
 1997 12  7833·
 1997 11  78861.
 1997 10  84866.
 1997 09  66832·
 1997 08  12817·
 1997 07  26793·
 1997 06  38808.
 1997 05  23812·
 1997 04  56824·
 1997 03  90856.
 1997 02  54841.
 1997 01  82852.
 1996 12 65859.
 1996 11 25884.
 1996 10 19843·
 1996 09 63829.
 1996 08 89803·
 1996 07 14817.
 1996 06 46809·
 1996 05 11800·
 1996 04 4821.
 1996 03 63827·
 1996 02 73839.
 1996 01 94875·
 1995 12  9849·
 1995 11  3821.
 1995 10  64817.
 1995 09  7794.
 1995 08  31802·
 1995 07  93806·
 1995 06  5781.
 1995 05  68796.
 1995 04  20812·
 1995 03  12818·
 1995 02  10846.
 1995 01  22834.
 1994 12 51787.
 1994 11 68766·
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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: Population Level: 55-64 years, Hispanic or Latino Women: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
   Transform this series  |  Display series in COPY/PASTE format  |  More series like this one

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