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 Series Title: Employment Level: Multiple Jobholders 20-24 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 46407.
 1994 02 17429.
 1994 03 15423·
 1994 04 66454·
 1994 05 23492.
 1994 06 40465.
 1994 07 73527.
 1994 08 8445·
 1994 09 10427.
 1994 10 6449.
 1994 11 76455.
 1994 12 92454.
 1995 01  58413.
 1995 02  95418.
 1995 03  37415.
 1995 04  63432.
 1995 05  42384.
 1995 06  14433.
 1995 07  94435.
 1995 08  89454.
 1995 09  61406·
 1995 10  96404·
 1995 11  8424·
 1995 12  66475·
 1996 01 43335·
 1996 02 97423·
 1996 03 69457·
 1996 04 11347.
 1996 05 36339.
 1996 06 98425.
 1996 07 89432.
 1996 08 69404.
 1996 09 17440.
 1996 10 6467·
 1996 11 6480.
 1996 12 10507·
 1997 01  86415·
 1997 02  53448·
 1997 03  83399·
 1997 04  27418.
 1997 05  68414·
 1997 06  95408·
 1997 07  7405·
 1997 08  40333.
 1997 09  13402·
 1997 10  14470·
 1997 11  93490·
 1997 12  92486.
 1998 01 98429.
 1998 02 17447·
 1998 03 77389·
 1998 04 53432.
 1998 05 22409·
 1998 06 35422·
 1998 07 22455.
 1998 08 17378.
 1998 09 11447·
 1998 10 25425.
 1998 11 17429·
 1998 12 3432·
 1999 01  14374.
 1999 02  68405.
 1999 03  73467.
 1999 04  56396·
 1999 05  9448·
 1999 06  72355·
 1999 07  31411·
 1999 08  43402.
 1999 09  94395·
 1999 10  67439·
 1999 11  51375.
 1999 12  61452·
 2000 01 96349.
 2000 02 11356·
 2000 03 22419·
 2000 04 27411·
 2000 05 64402.
 2000 06 85407.
 2000 07 56426·
 2000 08 86393.
 2000 09 75384·
 2000 10 96420·
 2000 11 93447.
 2000 12 6464.
 2001 01  28384·
 2001 02  75422.
 2001 03  94413.
 2001 04  83370·
 2001 05  49417·
 2001 06  80424·
 2001 07  47443·
 2001 08  35404.
 2001 09  88369.
 2001 10  90396·
 2001 11  66408.
 2001 12  7403.
 2002 01 21385·
 2002 02 15489·
 2002 03 88443·
 2002 04 66394.
 2002 05 48330·
 2002 06 84383.
 2002 07 77414·
 2002 08 9380·
 2002 09 95385.
 2002 10 55411·
 2002 11 19435·
 2002 12 53413·
 2003 01  11407.
 2003 02  9422·
 2003 03  28373.
 2003 04  44401·
 2003 05  73427·
 2003 06  52453·
 2003 07  42440.
 2003 08  49405.
 2003 09  80442.
 2003 10  18442.
 2003 11  24457·
 2003 12  64467.
 2004 01 58409·
 2004 02 61463·
 2004 03 61434·
 2004 04 7396·
 2004 05 58412.
 2004 06 65425.
 2004 07 67399.
 2004 08 22410.
 2004 09 54423.
 2004 10 34435·
 2004 11 79400·
 2004 12 79418.
 2005 01  48406·
 2005 02  2364.
 2005 03  61429·
 2005 04  72394·
 2005 05  64436·
 2005 06  25436.
 2005 07  99442.
 2005 08  19436·
 2005 09  53410·
 2005 10  84416.
 2005 11  8456.
 2005 12  66476·
 2006 01 91412.
 2006 02 86412·
 2006 03 25433·
 2006 04 81403.
 2006 05 77473·
 2006 06 62430·
 2006 07 12439.
 2006 08 59413.
 2006 09 38453·
 2006 10 70423·
 2006 11 58448.
 2006 12 17446·
 2007 01  23438·
 2007 02  91423·
 2007 03  76481.
 2007 04  2393.
 2007 05  8448·
 2007 06  31494·
 2007 07  4415.
 2007 08  81384·
 2007 09  93419·
 2007 10  23410.
 2007 11  3418.
 2007 12  49420.
 2008 01 4337·
 2008 02 22417.
 2008 03 63384.
 2008 04 25418·
 2008 05 92446·
 2008 06 11467.
 2008 07 96466·
 2008 08 53398·
 2008 09 30402·
 2008 10 96464·
 2008 11 41461·
 2008 12 3419·
 2009 01  21369.
 2009 02  9427.
 2009 03  59392·
 2009 04  68418·
 2009 05  89395.
 2009 06  6410·
 2009 07  39420.
 2009 08  68362·
 2009 09  84376.
 2009 10  69377.
 2009 11  94449.
 2009 12  46443·
 2010 01 83350.
 2010 02 5410.
 2010 03 61355.
 2010 04 72396·
 2010 05 84414.
 2010 06 45413·
 2010 07 4378.
 2010 08 41390.
 2010 09 15446·
 2010 10 46433·
 2010 11 10426.
 2010 12 70461·
 2011 01  25376·
 2011 02  90392.
 2011 03  93333.
 2011 04  5376·
 2011 05  90412.
 2011 06  83418.
 2011 07  90443·
 2011 08  14418·
 2011 09  10385·
 2011 10  57438·
 2011 11  64467.
 2011 12  92384.
 2012 01 10452·
 2012 02 68484·
 2012 03 2473·
 2012 04 57431·
 2012 05 41441.
 2012 06 99377.
 2012 07 19457.
 2012 08 55444·
 2012 09 78346·
 2012 10 55368.
 2012 11 52403·
 2012 12 53453·
 2013 01  21471·
 2013 02  69544.
 2013 03  63450·
 2013 04  47436.
 2013 05  97440.
 2013 06  97433·
 2013 07  40445.
 2013 08  54404·
 2013 09  55423.
 2013 10  21488.
 2013 11  97461.
 2013 12  21507.
 2014 01 71418·
 2014 02 47472·
 2014 03 72388·
 2014 04 14427·
 2014 05 44444·
 2014 06 7416.
 2014 07 26431·
 2014 08 30421.
 2014 09 2509·
 2014 10 58575·
 2014 11 49532·
 2014 12 86545·
 2015 01  93482·
 2015 02  81439.
 2015 03  53480·
 2015 04  28414.
 2015 05  94449·
 2015 06  83436·
 2015 07  75445·
 2015 08  23424·
 2015 09  4429·
 2015 10  96483·
 2015 11  80592·
 2015 12  67570.
 2016 01 49484.
 2016 02 75520.
 2016 03 54466·
 2016 04 78496·
 2016 05 80506.
 2016 06 4506·
 2016 07 10507·
 2016 08 1514·
 2016 09 72551·
 2016 10 88539.
 2016 11 87604.
 2016 12 4472.
 2017 01  25444·
 2017 02  59481·
 2017 03  48563·
 2017 04  83485.
 2017 05  64453·
 2017 06  75566.


 2017 07  79488.
 2017 08  55440·
 2017 09  41415.
 2017 10  15372.
 2017 11  95446·
 2017 12  65475.
 2018 01 30483·
 2018 02 88478.
 2018 03 32396.
 2018 04 83452·
 2018 05 32409.
 2018 06 24497.
 2018 07 55529.
 2018 08 2447·
 2018 09 72400·
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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 20-24 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

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