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 Series Title: Employment Level: Multiple Jobholders, Asian Women: NSA
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 2000 01 56135.
 2000 02 44124·
 2000 03 70133·
 2000 04 63147.
 2000 05 74111·
 2000 06 5797.
 2000 07 69113.
 2000 08 9589.
 2000 09 2114.
 2000 10 13113.
 2000 11 13129·
 2000 12 70124·
 2001 01  90133·
 2001 02  93133.
 2001 03  1595·
 2001 04  32112.
 2001 05  14107.
 2001 06  4111.
 2001 07  12115.
 2001 08  49121·
 2001 09  75115.
 2001 10  76113·
 2001 11  67141·
 2001 12  16121·
 2002 01 97135·
 2002 02 67146·
 2002 03 68119.
 2002 04 52135.
 2002 05 31127·
 2002 06 59122.
 2002 07 29118.
 2002 08 199.
 2002 09 52104.
 2002 10 58106·
 2002 11 86145·
 2002 12 32131.
 2003 01  62110.
 2003 02  9592·
 2003 03  497.
 2003 04  4096.
 2003 05  84123·
 2003 06  28130·
 2003 07  69107.
 2003 08  4393.
 2003 09  7085.
 2003 10  3874·
 2003 11  9593·
 2003 12  86107.
 2004 01 96110.
 2004 02 31162·
 2004 03 20113·
 2004 04 37143.
 2004 05 60108.
 2004 06 4075·
 2004 07 680·
 2004 08 9280.
 2004 09 8995.
 2004 10 2093·
 2004 11 41122·
 2004 12 69119·
 2005 01  34125.
 2005 02  54133·
 2005 03  38120.
 2005 04  12139·
 2005 05  69120.
 2005 06  49168·
 2005 07  36117·
 2005 08  90130.
 2005 09  95122·
 2005 10  35143·
 2005 11  97115.
 2005 12  98109·
 2006 01 37107·
 2006 02 69132·
 2006 03 8136·
 2006 04 5598·
 2006 05 46126.
 2006 06 34110.
 2006 07 84108.
 2006 08 4121.
 2006 09 9888·
 2006 10 35136·
 2006 11 61133·
 2006 12 16170.
 2007 01  91160.
 2007 02  5168.
 2007 03  2129·
 2007 04  83141·
 2007 05  53130.
 2007 06  0107.
 2007 07  97118·
 2007 08  26123.
 2007 09  33135.
 2007 10  1122.
 2007 11  56125·
 2007 12  88101·
 2008 01 6116.
 2008 02 16135.
 2008 03 19151·
 2008 04 38161·
 2008 05 74137·
 2008 06 76151·
 2008 07 48154.
 2008 08 72151·
 2008 09 61130·
 2008 10 37109.
 2008 11 31110·
 2008 12 7125.
 2009 01  18102·
 2009 02  82113.
 2009 03  81106.
 2009 04  87121·
 2009 05  20120.
 2009 06  17112.
 2009 07  35100·
 2009 08  83114·
 2009 09  68100.
 2009 10  7366·
 2009 11  5887·
 2009 12  8953·
 2010 01 87103·
 2010 02 783.
 2010 03 3691.
 2010 04 22126.
 2010 05 27120.
 2010 06 191·
 2010 07 82121·
 2010 08 28139·
 2010 09 64106.
 2010 10 61110.
 2010 11 35114.
 2010 12 7673·
 2011 01  9994.
 2011 02  20112.
 2011 03  57128·
 2011 04  59118.
 2011 05  56114·
 2011 06  33124.
 2011 07  3693.
 2011 08  9869.
 2011 09  86114.
 2011 10  82111.
 2011 11  86133·
 2011 12  35130·
 2012 01 64133.
 2012 02 75150.
 2012 03 43142.
 2012 04 41142.
 2012 05 91127.
 2012 06 4298·
 2012 07 71125·
 2012 08 9112.
 2012 09 92133·
 2012 10 40128·
 2012 11 58145·
 2012 12 58165·
 2013 01  18165.
 2013 02  52174·
 2013 03  16146.
 2013 04  33119.
 2013 05  43169·
 2013 06  83158·
 2013 07  84156·
 2013 08  3145·
 2013 09  69145.
 2013 10  65111.
 2013 11  24136.
 2013 12  61161.
 2014 01 21142.
 2014 02 55181.
 2014 03 25171·
 2014 04 28129·
 2014 05 49146.
 2014 06 34144.
 2014 07 99134·
 2014 08 47140·
 2014 09 28138·
 2014 10 10155·
 2014 11 84154.
 2014 12 87108·
 2015 01  59132·
 2015 02  13145·
 2015 03  42155·
 2015 04  43169·
 2015 05  67164.
 2015 06  1145.
 2015 07  63130·
 2015 08  33116·
 2015 09  4155·
 2015 10  55153.
 2015 11  58145.
 2015 12  2194·
 2016 01 43118·
 2016 02 81140·
 2016 03 67165·
 2016 04 19155·
 2016 05 85163·
 2016 06 12158.
 2016 07 50215·
 2016 08 78213.
 2016 09 57180.
 2016 10 4151.
 2016 11 97168.
 2016 12 98150·
 2017 01  7144·
 2017 02  38152·
 2017 03  20157·
 2017 04  24192·


 2017 05  13174·
 2017 06  22129.
 2017 07  58130·
 2017 08  23129·
 2017 09  73128.
 2017 10  87140·
 2017 11  72138·
 2017 12  92186·
 2018 01 14137.
 2018 02 89168.
 2018 03 52144·
 2018 04 48112.
 2018 05 85118.
 2018 06 10136·
 2018 07 9154·
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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, Asian 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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