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 Series Title: Employment Level: Multiple Jobholders, Asian Women: NSA
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 2000 01 18135.
 2000 02 52124·
 2000 03 21133.
 2000 04 45147·
 2000 05 70111·
 2000 06 4397·
 2000 07 14113·
 2000 08 6389.
 2000 09 50114·
 2000 10 94113.
 2000 11 70129.
 2000 12 43124.
 2001 01  11133.
 2001 02  88133.
 2001 03  395.
 2001 04  27112.
 2001 05  25107.
 2001 06  31111·
 2001 07  50115·
 2001 08  87121·
 2001 09  95115·
 2001 10  55113·
 2001 11  74141.
 2001 12  14121·
 2002 01 45135.
 2002 02 16146.
 2002 03 63119·
 2002 04 30135·
 2002 05 26127·
 2002 06 97122.
 2002 07 29118·
 2002 08 7799·
 2002 09 13104·
 2002 10 3106·
 2002 11 12145.
 2002 12 26131·
 2003 01  6110·
 2003 02  6792.
 2003 03  7397.
 2003 04  6996.
 2003 05  32123·
 2003 06  45130.
 2003 07  1107.
 2003 08  2793·
 2003 09  4085·
 2003 10  1974.
 2003 11  893·
 2003 12  43107·
 2004 01 6110·
 2004 02 95162·
 2004 03 32113.
 2004 04 87143·
 2004 05 30108.
 2004 06 575.
 2004 07 3780·
 2004 08 5380·
 2004 09 3795·
 2004 10 693.
 2004 11 9122.
 2004 12 59119.
 2005 01  78125.
 2005 02  79133.
 2005 03  63120·
 2005 04  50139·
 2005 05  29120·
 2005 06  31168.
 2005 07  36117.
 2005 08  96130.
 2005 09  89122.
 2005 10  93143·
 2005 11  90115.
 2005 12  90109·
 2006 01 84107.
 2006 02 23132·
 2006 03 14136·
 2006 04 5198.
 2006 05 65126.
 2006 06 2110·
 2006 07 20108.
 2006 08 24121.
 2006 09 788·
 2006 10 36136·
 2006 11 47133.
 2006 12 77170·
 2007 01  10160.
 2007 02  57168·
 2007 03  58129.
 2007 04  5141·
 2007 05  0130.
 2007 06  22107·
 2007 07  39118.
 2007 08  28123·
 2007 09  26135·
 2007 10  13122.
 2007 11  5125.
 2007 12  88101.
 2008 01 65116.
 2008 02 35135·
 2008 03 93151.
 2008 04 56161.
 2008 05 17137.
 2008 06 21151.
 2008 07 65154·
 2008 08 25151.
 2008 09 7130·
 2008 10 28109.
 2008 11 10110·
 2008 12 14125·
 2009 01  86102·
 2009 02  37113.
 2009 03  41106·
 2009 04  69121.
 2009 05  29120·
 2009 06  54112·
 2009 07  96100.
 2009 08  57114.
 2009 09  36100·
 2009 10  1166·
 2009 11  3787·
 2009 12  7353.
 2010 01 33103.
 2010 02 6683.
 2010 03 5291·
 2010 04 36126.
 2010 05 70120·
 2010 06 9991·
 2010 07 55121.
 2010 08 90139·
 2010 09 23106·
 2010 10 17110.
 2010 11 83114·
 2010 12 573·
 2011 01  9194.
 2011 02  52112·
 2011 03  99128·
 2011 04  74118.
 2011 05  1114·
 2011 06  60124.
 2011 07  9093·
 2011 08  1769.
 2011 09  3114.
 2011 10  24111·
 2011 11  71133.
 2011 12  78130.
 2012 01 72133·
 2012 02 49150·
 2012 03 78142.
 2012 04 25142·
 2012 05 8127·
 2012 06 6798·
 2012 07 75125·
 2012 08 54112·
 2012 09 37133·
 2012 10 36128.
 2012 11 49145.
 2012 12 83165·
 2013 01  9165.
 2013 02  36174.
 2013 03  13146.
 2013 04  57119·
 2013 05  1169.
 2013 06  75158·
 2013 07  6156·
 2013 08  43145·
 2013 09  11145.
 2013 10  84111.
 2013 11  90136·
 2013 12  38161.
 2014 01 66142·
 2014 02 19181·
 2014 03 53171.
 2014 04 59129·
 2014 05 15146·
 2014 06 62144·
 2014 07 8134.
 2014 08 52140.
 2014 09 35138·
 2014 10 21155.
 2014 11 93154.
 2014 12 84108·
 2015 01  25132.
 2015 02  26145.
 2015 03  70155.
 2015 04  50169·
 2015 05  12164·
 2015 06  33145.
 2015 07  28130·
 2015 08  70116·
 2015 09  45155.
 2015 10  26153·
 2015 11  80145·
 2015 12  88194·
 2016 01 99118·
 2016 02 10140·
 2016 03 63165·
 2016 04 72155·
 2016 05 76163·
 2016 06 18158·
 2016 07 40215·
 2016 08 16213·
 2016 09 1180.
 2016 10 5151·
 2016 11 99168·
 2016 12 41150·
 2017 01  23144.
 2017 02  53152·


 2017 03  54157·
 2017 04  90192·
 2017 05  19174.
 2017 06  70129.
 2017 07  41130.
 2017 08  32129.
 2017 09  89128.
 2017 10  86140.
 2017 11  24138·
 2017 12  61186.
 2018 01 57137.
 2018 02 58168·
 2018 03 91144·
 2018 04 97112.
 2018 05 76118.
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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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