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 Series Title: Multiple Jobholders as a Percent of Employed, Asian Women: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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 2012 04 264·0
 2012 03 573.9
 2012 02 444.2
 2012 01 523·6
 2011 12  734.0
 2011 11  964·1
 2011 10  153.5
 2011 09  543.7
 2011 08  172·2
 2011 07  652.9
 2011 06  193.9
 2011 05  863.6
 2011 04  93·7
 2011 03  454.0
 2011 02  683·6
 2011 01  923·0
 2010 12 242·3
 2010 11 443·6
 2010 10 03.5
 2010 09 413.4
 2010 08 634·4
 2010 07 923·9
 2010 06 782.9
 2010 05 273·8
 2010 04 524·0
 2010 03 463.0
 2010 02 892·7
 2010 01 703·5
 2009 12  391.7
 2009 11  882.9
 2009 10  472·2
 2009 09  133.3
 2009 08  23·7
 2009 07  253.2
 2009 06  903.6
 2009 05  263·8
 2009 04  403.9
 2009 03  883·4
 2009 02  803·7
 2009 01  33·4
 2008 12 793.9
 2008 11 343.5
 2008 10 53.5
 2008 09 634·1
 2008 08 694.7
 2008 07 444.8
 2008 06 784·7
 2008 05 514·3
 2008 04 854.9
 2008 03 264·6
 2008 02 384·1
 2008 01 343.6
 2007 12  283·1
 2007 11  103.9
 2007 10  463.9
 2007 09  84.3
 2007 08  243.9
 2007 07  543.7
 2007 06  913.4
 2007 05  924.1
 2007 04  224·5
 2007 03  384.1
 2007 02  865.4
 2007 01  295·2
 2006 12 985.5
 2006 11 714.3
 2006 10 694.5
 2006 09 893·0
 2006 08 534·1
 2006 07 823.6
 2006 06 23.7
 2006 05 674·2
 2006 04 123·3
 2006 03 304.5
 2006 02 744·4
 2006 01 803.7
 2005 12  243.7
 2005 11  953.9
 2005 10  964.9
 2005 09  744·2
 2005 08  674·5
 2005 07  854.1
 2005 06  95.7
 2005 05  174·2
 2005 04  394·9
 2005 03  304·2
 2005 02  734·7
 2005 01  44·4
 2004 12 674.2
 2004 11 884.3
 2004 10 773.3
 2004 09 533·5
 2004 08 12.9
 2004 07 402·9
 2004 06 342·8
 2004 05 104·0
 2004 04 165.2
 2004 03 934.2
 2004 02 816·0
 2004 01 424·0
 2003 12  123·8
 2003 11  793·4
 2003 10  832.7
 2003 09  453·2
 2003 08  153·5
 2003 07  533·9
 2003 06  264.8
 2003 05  364·6
 2003 04  763.7
 2003 03  983·7
 2003 02  233.6
 2003 01  624·2
 2002 12 694·5
 2002 11 214.9
 2002 10 133.7
 2002 09 903.6
 2002 08 963.5
 2002 07 524·1
 2002 06 574·3
 2002 05 144·5
 2002 04 814.8
 2002 03 504.3
 2002 02 455.1
 2002 01 544·7
 2001 12  754.2
 2001 11  944.9
 2001 10  894.0
 2001 09  554·1
 2001 08  534·4
 2001 07  934·1
 2001 06  274.0
 2001 05  843·7
 2001 04  163·9
 2001 03  773·3
 2001 02  224·7
 2001 01  374.7
 2000 12 894·4
 2000 11 34.5
 2000 10 613.9
 2000 09 324·0
 2000 08 233·1
 2000 07 534.0
 2000 06 583·5
 2000 05 143.9
 2000 04 925·3
 2000 03 344·9
 2000 02 504.6
 2000 01 515.1
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US Unemployment Rate: Alternative Measures of Labor Underutilization

Charts

Unemployment Rate: US Unemployment Rate: 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, 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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