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 Series Title: Employment Level: Multiple Jobholders 55-64 years, Women: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Yearly Chart  |  Excel file  |  Self-updating Excel file
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 1994 01 34223·
 1994 02 15228.
 1994 03 88216.
 1994 04 30188.
 1994 05 44187·
 1994 06 33209·
 1994 07 3188.
 1994 08 91205·
 1994 09 13220·
 1994 10 42222·
 1994 11 14249.
 1994 12 45242.
 1995 01  92216·
 1995 02  26218.
 1995 03  31236.
 1995 04  35246·
 1995 05  58239.
 1995 06  90221·
 1995 07  95210.
 1995 08  31239·
 1995 09  10248.
 1995 10  67291·
 1995 11  66238·
 1995 12  27257.
 1996 01 73201.
 1996 02 12250·
 1996 03 34224·
 1996 04 42201·
 1996 05 99244·
 1996 06 7235.
 1996 07 11248.
 1996 08 20237.
 1996 09 62248·
 1996 10 60272·
 1996 11 35224.
 1996 12 30235·
 1997 01  62237.
 1997 02  1280·
 1997 03  69294·
 1997 04  67281·
 1997 05  26299·
 1997 06  88267·
 1997 07  1252.
 1997 08  49263·
 1997 09  4292·
 1997 10  2278.
 1997 11  43251.
 1997 12  21228·
 1998 01 71270.
 1998 02 49318·
 1998 03 34295.
 1998 04 51324·
 1998 05 26281·
 1998 06 62239.
 1998 07 36252.
 1998 08 35290.
 1998 09 97309·
 1998 10 96355·
 1998 11 38345.
 1998 12 91363.
 1999 01  33325·
 1999 02  34345.
 1999 03  52324.
 1999 04  62309.
 1999 05  10291·
 1999 06  82273.
 1999 07  16281·
 1999 08  20243.
 1999 09  27287.
 1999 10  72373·
 1999 11  93355·
 1999 12  57359.
 2000 01 11316.
 2000 02 61383.
 2000 03 71362.
 2000 04 92313.
 2000 05 11313.
 2000 06 29276.
 2000 07 63335·
 2000 08 70301.
 2000 09 4323.
 2000 10 85306·
 2000 11 6340.
 2000 12 61333·
 2001 01  89332·
 2001 02  58354.
 2001 03  64369·
 2001 04  57337.
 2001 05  92334·
 2001 06  7321·
 2001 07  25302·
 2001 08  79285·
 2001 09  63296.
 2001 10  13306.
 2001 11  1352.
 2001 12  70318·
 2002 01 78323·
 2002 02 81348.
 2002 03 30380·
 2002 04 99367·
 2002 05 37371·
 2002 06 45323·
 2002 07 75317.
 2002 08 61326·
 2002 09 66371·
 2002 10 60355.
 2002 11 25386·
 2002 12 75427.
 2003 01  14372.
 2003 02  9441·
 2003 03  91452.
 2003 04  85386·
 2003 05  58403.
 2003 06  97377·
 2003 07  12353.
 2003 08  60396.
 2003 09  97402.
 2003 10  57461.
 2003 11  51437.
 2003 12  94403·
 2004 01 57419·
 2004 02 45466·
 2004 03 95459.
 2004 04 6419.
 2004 05 89394.
 2004 06 43379·
 2004 07 58389·
 2004 08 41398.
 2004 09 68418.
 2004 10 57435·
 2004 11 77401·
 2004 12 68431.
 2005 01  93407·
 2005 02  20443.
 2005 03  16482·
 2005 04  80479·
 2005 05  92440·
 2005 06  87411·
 2005 07  62374.
 2005 08  97345·
 2005 09  13462·
 2005 10  40422.
 2005 11  27418·
 2005 12  64433·
 2006 01 32417·
 2006 02 87511.
 2006 03 51515·
 2006 04 48482.
 2006 05 51487·
 2006 06 58421.
 2006 07 95477.
 2006 08 45457·
 2006 09 93478.
 2006 10 10470·
 2006 11 49491.
 2006 12 73451.
 2007 01  10487.
 2007 02  25539·
 2007 03  23536·
 2007 04  77531·
 2007 05  78484.
 2007 06  10459·
 2007 07  58440·
 2007 08  26429.
 2007 09  95503.
 2007 10  96553·
 2007 11  15523.
 2007 12  14525.
 2008 01 88562.
 2008 02 40557·
 2008 03 82513.
 2008 04 59497·
 2008 05 7534.
 2008 06 24505·
 2008 07 72521.
 2008 08 7540·
 2008 09 28547·
 2008 10 53515.
 2008 11 23548.
 2008 12 26493.
 2009 01  50577·
 2009 02  60637.
 2009 03  98603.
 2009 04  11626·
 2009 05  0538·
 2009 06  2473·
 2009 07  85501·
 2009 08  80482·
 2009 09  28434·
 2009 10  60512.
 2009 11  97524.
 2009 12  78471·
 2010 01 8564·
 2010 02 40557.
 2010 03 71585.
 2010 04 74567·
 2010 05 42580·
 2010 06 75507.
 2010 07 71436.
 2010 08 61456·
 2010 09 55513.
 2010 10 21547.
 2010 11 85500.
 2010 12 60562.
 2011 01  97584.
 2011 02  59582·
 2011 03  24598·
 2011 04  15577.
 2011 05  44540·
 2011 06  96536.
 2011 07  28571·
 2011 08  93530.
 2011 09  96510·
 2011 10  65534.
 2011 11  59566.
 2011 12  91597.
 2012 01 78574·
 2012 02 21680.
 2012 03 5611.
 2012 04 26593·
 2012 05 41636·
 2012 06 46565.
 2012 07 79483.
 2012 08 43544.
 2012 09 60538·
 2012 10 47585·
 2012 11 18621.
 2012 12 11605·
 2013 01  35533·
 2013 02  55550.
 2013 03  87553.
 2013 04  24567.
 2013 05  93609.
 2013 06  28524·
 2013 07  71494·
 2013 08  1567.
 2013 09  83550.
 2013 10  46618·
 2013 11  85574.
 2013 12  87544·
 2014 01 81565·
 2014 02 17569.
 2014 03 67650·
 2014 04 50681.
 2014 05 87564·
 2014 06 71581·
 2014 07 78505.
 2014 08 85534.
 2014 09 26563·
 2014 10 67598·
 2014 11 8620.
 2014 12 11632·
 2015 01  49549·
 2015 02  84554·
 2015 03  69543·
 2015 04  72576.
 2015 05  32564·
 2015 06  31563.
 2015 07  98564·
 2015 08  37540.
 2015 09  74584.
 2015 10  38643·
 2015 11  60584.
 2015 12  0634·
 2016 01 2559.
 2016 02 62569·
 2016 03 41599·
 2016 04 81569·
 2016 05 64647.
 2016 06 85589·
 2016 07 54547·
 2016 08 23544·
 2016 09 38614·
 2016 10 14636.
 2016 11 38602.
 2016 12 96595.
 2017 01  23537·
 2017 02  80547.
 2017 03  56582.
 2017 04  94562.
 2017 05  45576.
 2017 06  40573.


 2017 07  94537.
 2017 08  36559·
 2017 09  54550.
 2017 10  75548·
 2017 11  67570·
 2017 12  66612.
 2018 01 25529.
 2018 02 92607·
 2018 03 12530.
 2018 04 53558.
 2018 05 59590.
 2018 06 22622.
 2018 07 91634.
 2018 08 92609·
 2018 09 81644.
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US Unemployment Rate: Alternative Measures of Labor Underutilization

Charts

Unemployment Rate and 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: Employment Level: Multiple Jobholders 55-64 years, 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

New data set: Quarterly Financial Reporting: Manufacturing, Mining, Trade, and Selected Service Industries

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