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 Series Title: Multiple Jobholders as a Percent of Employed: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Yearly Chart  |  Excel file  |  Self-updating Excel file
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 1994 01 265·6
 1994 02 365.8
 1994 03 595·9
 1994 04 656·0
 1994 05 506.0
 1994 06 125.7
 1994 07 505·8
 1994 08 935.7
 1994 09 546.1
 1994 10 986.1
 1994 11 546·0
 1994 12 336.0
 1995 01  865.8
 1995 02  776.3
 1995 03  846.1
 1995 04  286·2
 1995 05  246·4
 1995 06  556.2
 1995 07  786·1
 1995 08  476.0
 1995 09  666·1
 1995 10  646·3
 1995 11  06·1
 1995 12  856·2
 1996 01 395·8
 1996 02 616.3
 1996 03 366.3
 1996 04 616.0
 1996 05 926·2
 1996 06 276·0
 1996 07 15·9
 1996 08 195.9
 1996 09 26·1
 1996 10 686.5
 1996 11 316·6
 1996 12 276·4
 1997 01  686.0
 1997 02  176·2
 1997 03  906.1
 1997 04  816.1
 1997 05  166.3
 1997 06  306·3
 1997 07  656·1
 1997 08  995.8
 1997 09  976·0
 1997 10  896.2
 1997 11  706.2
 1997 12  256.2
 1998 01 856.0
 1998 02 06.1
 1998 03 426·1
 1998 04 296.1
 1998 05 826.2
 1998 06 965·8
 1998 07 445.8
 1998 08 55·6
 1998 09 126.0
 1998 10 326.2
 1998 11 646.3
 1998 12 716·2
 1999 01  266.0
 1999 02  906·1
 1999 03  166·1
 1999 04  735·8
 1999 05  995.9
 1999 06  775.6
 1999 07  365·7
 1999 08  795·4
 1999 09  325.7
 1999 10  256·0
 1999 11  886.0
 1999 12  836.0
 2000 01 505·7
 2000 02 905.7
 2000 03 605.7
 2000 04 45.7
 2000 05 45.7
 2000 06 535·3
 2000 07 645·5
 2000 08 875·2
 2000 09 685.5
 2000 10 235·5
 2000 11 385.5
 2000 12 05·7
 2001 01  445.3
 2001 02  295.6
 2001 03  465.6
 2001 04  395.4
 2001 05  565·5
 2001 06  295.4
 2001 07  765·4
 2001 08  215.1
 2001 09  555·4
 2001 10  55·2
 2001 11  395·2
 2001 12  925·4
 2002 01 175·2
 2002 02 635.5
 2002 03 745.5
 2002 04 205·4
 2002 05 425·3
 2002 06 345.3
 2002 07 445·3
 2002 08 995.0
 2002 09 545·3
 2002 10 765·3
 2002 11 375.3
 2002 12 485·6
 2003 01  65·3
 2003 02  705.6
 2003 03  665.4
 2003 04  135.2
 2003 05  715·3
 2003 06  225·3
 2003 07  685.3
 2003 08  615.2
 2003 09  515·2
 2003 10  655.4
 2003 11  75·3
 2003 12  875·2
 2004 01 705.2
 2004 02 545·3
 2004 03 705.4
 2004 04 115.2
 2004 05 805.2
 2004 06 725.3
 2004 07 705·3
 2004 08 755·3
 2004 09 555.5
 2004 10 255·7
 2004 11 465·4
 2004 12 505·6
 2005 01  975·2
 2005 02  465.5
 2005 03  595·5
 2005 04  295.3
 2005 05  295.2
 2005 06  895.4
 2005 07  985.3
 2005 08  335·0
 2005 09  45.4
 2005 10  385.5
 2005 11  775.3
 2005 12  35.4
 2006 01 955.3
 2006 02 985·2
 2006 03 315.3
 2006 04 115.1
 2006 05 45·3
 2006 06 25.0
 2006 07 265·1
 2006 08 505·0
 2006 09 565.4
 2006 10 65.4
 2006 11 485·4
 2006 12 395·4
 2007 01  15·2
 2007 02  915·4
 2007 03  105·4
 2007 04  235.4
 2007 05  155·3
 2007 06  655.1
 2007 07  505·2
 2007 08  704.9
 2007 09  985·2
 2007 10  595.4
 2007 11  325·3
 2007 12  755.2
 2008 01 755.1
 2008 02 295.3
 2008 03 435·2
 2008 04 565.2
 2008 05 975.2
 2008 06 585·2
 2008 07 955·3
 2008 08 585.3
 2008 09 405.3
 2008 10 515.4
 2008 11 285.2
 2008 12 515·2
 2009 01  35.2
 2009 02  415·5
 2009 03  35.5
 2009 04  285·5
 2009 05  125.2
 2009 06  845·0
 2009 07  95.2
 2009 08  84·8
 2009 09  175.1
 2009 10  625·2
 2009 11  585.2
 2009 12  355.0
 2010 01 954.9
 2010 02 825.2
 2010 03 885·1
 2010 04 795.1
 2010 05 445.2
 2010 06 744·9
 2010 07 634·7
 2010 08 344·7
 2010 09 914·8
 2010 10 964·9
 2010 11 704.9
 2010 12 194.9
 2011 01  864·8
 2011 02  305·0
 2011 03  224.9
 2011 04  784·9
 2011 05  55·1
 2011 06  814.9
 2011 07  574·8
 2011 08  804.7
 2011 09  474·9
 2011 10  835·0
 2011 11  385.0
 2011 12  195.0
 2012 01 394.9
 2012 02 905.1
 2012 03 535.0
 2012 04 154.9
 2012 05 295·0
 2012 06 854.7
 2012 07 144.7
 2012 08 124·7
 2012 09 954.8
 2012 10 754·8
 2012 11 595.0
 2012 12 784.9
 2013 01  364·8
 2013 02  925.2
 2013 03  525.0
 2013 04  84·9
 2013 05  784·9
 2013 06  904·8
 2013 07  814.8
 2013 08  214·7
 2013 09  714.8
 2013 10  544.8
 2013 11  574·8
 2013 12  624.8
 2014 01 914·7
 2014 02 895·0
 2014 03 204.9
 2014 04 984·9
 2014 05 375.0
 2014 06 264·7
 2014 07 314.6
 2014 08 264·7
 2014 09 364.8
 2014 10 235·3
 2014 11 805.1
 2014 12 625.0
 2015 01  375.0
 2015 02  604.9
 2015 03  784·9
 2015 04  534.7
 2015 05  174.7
 2015 06  464·7
 2015 07  644.7
 2015 08  664·6
 2015 09  754.9
 2015 10  115.1
 2015 11  05.1
 2015 12  975·2
 2016 01 364.9
 2016 02 125·0
 2016 03 755.0
 2016 04 634·9
 2016 05 524.9
 2016 06 304·6
 2016 07 14.7
 2016 08 104.8
 2016 09 985·2
 2016 10 735·3
 2016 11 165.3
 2016 12 65.1
 2017 01  734.9
 2017 02  715.3
 2017 03  835.3
 2017 04  465·0
 2017 05  44.9
 2017 06  824·8


 2017 07  904.7
 2017 08  494·5
 2017 09  414.8
 2017 10  874·8
 2017 11  504·9
 2017 12  585·1
 2018 01 595.1
 2018 02 935·2
 2018 03 15.0
 2018 04 444·9
 2018 05 584·8
 2018 06 324·8
 2018 07 65.0
 2018 08 04·8
 2018 09 654.9
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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: 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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