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 Series Title: Population Level: 65 years and over, 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 851728·
 2012 03 11729.
 2012 02 71723.
 2012 01 881736.
 2011 12  521705.
 2011 11  91709.
 2011 10  721681.
 2011 09  811656·
 2011 08  611649.
 2011 07  911639·
 2011 06  121624·
 2011 05  471599·
 2011 04  611612.
 2011 03  281616.
 2011 02  411609·
 2011 01  321621·
 2010 12 281678·
 2010 11 271679·
 2010 10 961661.
 2010 09 31648·
 2010 08 631645·
 2010 07 191636.
 2010 06 411620.
 2010 05 551607.
 2010 04 901601·
 2010 03 611596·
 2010 02 641601·
 2010 01 71592.
 2009 12  611614.
 2009 11  351609.
 2009 10  771611·
 2009 09  41594·
 2009 08  511575·
 2009 07  471569.
 2009 06  181560·
 2009 05  141561·
 2009 04  601551.
 2009 03  291554·
 2009 02  511561·
 2009 01  321547.
 2008 12 131513.
 2008 11 381507.
 2008 10 621510·
 2008 09 771508·
 2008 08 611494.
 2008 07 541499·
 2008 06 651494.
 2008 05 931487·
 2008 04 791478·
 2008 03 861463·
 2008 02 991457·
 2008 01 491444·
 2007 12  681427·
 2007 11  641429·
 2007 10  251412·
 2007 09  391428·
 2007 08  531437.
 2007 07  461439·
 2007 06  311424·
 2007 05  821408.
 2007 04  841402.
 2007 03  121398.
 2007 02  311391·
 2007 01  231394.
 2006 12 371372·
 2006 11 701373·
 2006 10 621363·
 2006 09 301365.
 2006 08 121349.
 2006 07 501354.
 2006 06 881341.
 2006 05 981337·
 2006 04 351349.
 2006 03 111340·
 2006 02 961343.
 2006 01 461330.
 2005 12  561311·
 2005 11  331305·
 2005 10  991306.
 2005 09  191293·
 2005 08  501283·
 2005 07  231283·
 2005 06  341283.
 2005 05  841278.
 2005 04  181289·
 2005 03  121287.
 2005 02  661278.
 2005 01  371274.
 2004 12 861252.
 2004 11 581242.
 2004 10 811239·
 2004 09 961238.
 2004 08 21229·
 2004 07 411217·
 2004 06 931228·
 2004 05 61218.
 2004 04 441206.
 2004 03 701203.
 2004 02 401191.
 2004 01 351188·
 2003 12  111187.
 2003 11  741178·
 2003 10  841175·
 2003 09  791166.
 2003 08  291172.
 2003 07  111177.
 2003 06  131175·
 2003 05  551166·
 2003 04  471162·
 2003 03  631154·
 2003 02  401138.
 2003 01  91137·
 2002 12 431077.
 2002 11 361054·
 2002 10 31048.
 2002 09 91070.
 2002 08 151036.
 2002 07 611042.
 2002 06 661073·
 2002 05 491064.
 2002 04 891079·
 2002 03 971091.
 2002 02 151093·
 2002 01 491084.
 2001 12  161094·
 2001 11  231081·
 2001 10  641004.
 2001 09  531007.
 2001 08  721000·
 2001 07  461013·
 2001 06  501067.
 2001 05  301093.
 2001 04  551083.
 2001 03  991037.
 2001 02  371038·
 2001 01  731002.
 2000 12 93996·
 2000 11 391012·
 2000 10 13993·
 2000 09 3965.
 2000 08 34985.
 2000 07 45999.
 2000 06 901012·
 2000 05 63995.
 2000 04 56968.
 2000 03 26956·
 2000 02 5950.
 2000 01 23956·
 1999 12  571012·
 1999 11  131035.
 1999 10  241003·
 1999 09  76982·
 1999 08  641013.
 1999 07  62968·
 1999 06  32964·
 1999 05  42941.
 1999 04  26890·
 1999 03  56883.
 1999 02  42953.
 1999 01  65980·
 1998 12 201013·
 1998 11 0997.
 1998 10 94975.
 1998 09 14972·
 1998 08 45948·
 1998 07 27954.
 1998 06 49940·
 1998 05 82922.
 1998 04 27881·
 1998 03 93873·
 1998 02 96920·
 1998 01 91981.
 1997 12  17956·
 1997 11  79916.
 1997 10  47924·
 1997 09  82937.
 1997 08  89899·
 1997 07  93906.
 1997 06  41893·
 1997 05  27884·
 1997 04  45894·
 1997 03  66876·
 1997 02  40901.
 1997 01  17900.
 1996 12 9886·
 1996 11 55882.
 1996 10 31930.
 1996 09 74898·
 1996 08 32917.
 1996 07 41901.
 1996 06 29883.
 1996 05 41897.
 1996 04 89866·
 1996 03 31868.
 1996 02 71837.
 1996 01 87820.
 1995 12  81824.
 1995 11  56826·
 1995 10  19836·
 1995 09  6826.
 1995 08  33863.
 1995 07  74846·
 1995 06  63878.
 1995 05  18843·
 1995 04  95807·
 1995 03  65770.
 1995 02  13732·
 1995 01  66768·
 1994 12 44796·
 1994 11 38778.
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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: 65 years and over, 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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