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 Series Title: Multiple Jobholders as a Percent of Employed, 16-19 years, Men: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Yearly Chart  |  Excel file  |  Self-updating Excel file
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 1994 01 782·6
 1994 02 352·5
 1994 03 32·6
 1994 04 915·1
 1994 05 334·9
 1994 06 634·6
 1994 07 186.2
 1994 08 665.9
 1994 09 542·7
 1994 10 893·2
 1994 11 333·2
 1994 12 394·2
 1995 01  923·6
 1995 02  953.2
 1995 03  633·1
 1995 04  554.6
 1995 05  224·4
 1995 06  887·0
 1995 07  447.0
 1995 08  825.4
 1995 09  454·3
 1995 10  994.3
 1995 11  393·3
 1995 12  163.9
 1996 01 853·4
 1996 02 854·3
 1996 03 374·1
 1996 04 753·9
 1996 05 945.1
 1996 06 285·8
 1996 07 515·5
 1996 08 44.6
 1996 09 474.4
 1996 10 343·3
 1996 11 173.9
 1996 12 713.9
 1997 01  434·9
 1997 02  353.5
 1997 03  03·8
 1997 04  703.5
 1997 05  94.0
 1997 06  885·8
 1997 07  875.4
 1997 08  224.1
 1997 09  953·5
 1997 10  743·8
 1997 11  913·9
 1997 12  694·0
 1998 01 763·3
 1998 02 03·6
 1998 03 493.3
 1998 04 813.8
 1998 05 534.0
 1998 06 974.8
 1998 07 265.5
 1998 08 534·2
 1998 09 513·1
 1998 10 232·9
 1998 11 83.2
 1998 12 34.0
 1999 01  203·3
 1999 02  583.4
 1999 03  82·5
 1999 04  753·6
 1999 05  363·9
 1999 06  104.8
 1999 07  656.0
 1999 08  395·8
 1999 09  993.9
 1999 10  103.7
 1999 11  414.1
 1999 12  893.6
 2000 01 352.2
 2000 02 152.9
 2000 03 243·0
 2000 04 443·4
 2000 05 943.9
 2000 06 65.4
 2000 07 275.3
 2000 08 484·5
 2000 09 513.7
 2000 10 903.8
 2000 11 883·3
 2000 12 703.8
 2001 01  72·5
 2001 02  983·8
 2001 03  703.3
 2001 04  43·4
 2001 05  873.8
 2001 06  884·4
 2001 07  614.6
 2001 08  704.6
 2001 09  423.1
 2001 10  413.2
 2001 11  732·7
 2001 12  113.3
 2002 01 463·1
 2002 02 632.4
 2002 03 453·6
 2002 04 984·0
 2002 05 13·1
 2002 06 874.1
 2002 07 394·6
 2002 08 234.0
 2002 09 324·0
 2002 10 684·1
 2002 11 443·0
 2002 12 62·9
 2003 01  881·8
 2003 02  892·9
 2003 03  722·6
 2003 04  913·1
 2003 05  463.8
 2003 06  564.8
 2003 07  606.0
 2003 08  484.8
 2003 09  63.4
 2003 10  13.6
 2003 11  733·3
 2003 12  703·0
 2004 01 942·6
 2004 02 803.6
 2004 03 983·0
 2004 04 773·7
 2004 05 593·7
 2004 06 754·0
 2004 07 475.0
 2004 08 124.6
 2004 09 773·5
 2004 10 932·6
 2004 11 593.2
 2004 12 453.1
 2005 01  483.1
 2005 02  653.0
 2005 03  963·1
 2005 04  713·9
 2005 05  993·9
 2005 06  496.1
 2005 07  475·9
 2005 08  75.3
 2005 09  783·9
 2005 10  243·3
 2005 11  243.2
 2005 12  992.5
 2006 01 623·5
 2006 02 992.5
 2006 03 662.2
 2006 04 152.7
 2006 05 522.6
 2006 06 54.3
 2006 07 345.1
 2006 08 503.3
 2006 09 713·1
 2006 10 993.3
 2006 11 173.7
 2006 12 223·3
 2007 01  722·2
 2007 02  612·1
 2007 03  292.7
 2007 04  773·4
 2007 05  283·6
 2007 06  03.7
 2007 07  64·4
 2007 08  823.5
 2007 09  412·3
 2007 10  464.0
 2007 11  113·8
 2007 12  333·2
 2008 01 372·7
 2008 02 562·6
 2008 03 342.0
 2008 04 483.5
 2008 05 643·6
 2008 06 124·1
 2008 07 854·4
 2008 08 713·7
 2008 09 993.9
 2008 10 204.2
 2008 11 43.5
 2008 12 722.6
 2009 01  432.8
 2009 02  122·4
 2009 03  533·1
 2009 04  443·8
 2009 05  192·9
 2009 06  453·3
 2009 07  204.4
 2009 08  82.7
 2009 09  803·0
 2009 10  03.1
 2009 11  192·5
 2009 12  62·2
 2010 01 02·7
 2010 02 842·6
 2010 03 862·6
 2010 04 92·5
 2010 05 802·8
 2010 06 283.9
 2010 07 853·5
 2010 08 103·0
 2010 09 451·6
 2010 10 903.6
 2010 11 33.1
 2010 12 282.1
 2011 01  452·8
 2011 02  512·4
 2011 03  542·8
 2011 04  84·1
 2011 05  573.2
 2011 06  175.3
 2011 07  765.1
 2011 08  184.9
 2011 09  793·3
 2011 10  203·6
 2011 11  313.8
 2011 12  532·4
 2012 01 382.0
 2012 02 173.0
 2012 03 73.9
 2012 04 333.4
 2012 05 853.4
 2012 06 903.2
 2012 07 173.7
 2012 08 04·2
 2012 09 933.9
 2012 10 453.2
 2012 11 993·6
 2012 12 252·8
 2013 01  652·7
 2013 02  132.8
 2013 03  162·9
 2013 04  12.9
 2013 05  244·5
 2013 06  515.8
 2013 07  565.3
 2013 08  473.7
 2013 09  233.1
 2013 10  423.7
 2013 11  323.4
 2013 12  94·4
 2014 01 352·8
 2014 02 912·7
 2014 03 813·2
 2014 04 543.1
 2014 05 623.7
 2014 06 315·0
 2014 07 664·6
 2014 08 773.8
 2014 09 285·2
 2014 10 173·7
 2014 11 763·1
 2014 12 971·9
 2015 01  853.2
 2015 02  322·9
 2015 03  232.1
 2015 04  582.6
 2015 05  72.9
 2015 06  823.7
 2015 07  453.9
 2015 08  303.9
 2015 09  953.6
 2015 10  993.1
 2015 11  62·5
 2015 12  72·3
 2016 01 742.0
 2016 02 403·0
 2016 03 922.6
 2016 04 63·2
 2016 05 963·2
 2016 06 853·3
 2016 07 173·4
 2016 08 743·6
 2016 09 343·1
 2016 10 424·4
 2016 11 193·2
 2016 12 793.9
 2017 01  904·0
 2017 02  433.6
 2017 03  602.8
 2017 04  153·1


 2017 05  882.8
 2017 06  444.8
 2017 07  293.3
 2017 08  13.5
 2017 09  803.0
 2017 10  262·9
 2017 11  382·9
 2017 12  812.1
 2018 01 412·5
 2018 02 971·7
 2018 03 252·5
 2018 04 252.1
 2018 05 712.5
 2018 06 883.6
 2018 07 543·4
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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: Multiple Jobholders as a Percent of Employed, 16-19 years, Men: 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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