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 Series Title: Employed: Wage and salary workers, Real estate and rental and leasing, Women: NSA
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 2000 01 951054.
 2000 02 191066.
 2000 03 451051·
 2000 04 321137.
 2000 05 631136·
 2000 06 221225·
 2000 07 981178·
 2000 08 71183·
 2000 09 471133·
 2000 10 741080.
 2000 11 21072.
 2000 12 311041·
 2001 01  991016·
 2001 02  561079·
 2001 03  691127.
 2001 04  481101.
 2001 05  921220·
 2001 06  751211·
 2001 07  391207·
 2001 08  261194·
 2001 09  281145·
 2001 10  621097·
 2001 11  731112·
 2001 12  611149.
 2002 01 321179·
 2002 02 741180.
 2002 03 591204·
 2002 04 711198·
 2002 05 541267.
 2002 06 921255·
 2002 07 111123.
 2002 08 01097.
 2002 09 691126.
 2002 10 241101·
 2002 11 661118·
 2002 12 171098.
 2003 01  791105·
 2003 02  11140·
 2003 03  871136·
 2003 04  181166·
 2003 05  91169·
 2003 06  801225·
 2003 07  621221.
 2003 08  201162.
 2003 09  81156.
 2003 10  421079.
 2003 11  41114.
 2003 12  681167·
 2004 01 521108·
 2004 02 931170.
 2004 03 511162.
 2004 04 311176·
 2004 05 421198·
 2004 06 661197.
 2004 07 651240·
 2004 08 41212·
 2004 09 31224·
 2004 10 181287.
 2004 11 351232.
 2004 12 41202.
 2005 01  861218.
 2005 02  291230.
 2005 03  741262·
 2005 04  781371·
 2005 05  651252.
 2005 06  71222.
 2005 07  191267.
 2005 08  921275.
 2005 09  421343·
 2005 10  821405·
 2005 11  331401·
 2005 12  431366.
 2006 01 411310.
 2006 02 131326·
 2006 03 51368.
 2006 04 491364·
 2006 05 131398·
 2006 06 791384.
 2006 07 461347.
 2006 08 531287.
 2006 09 331271·
 2006 10 891310·
 2006 11 961338·
 2006 12 261335.
 2007 01  21287.
 2007 02  731303.
 2007 03  161340·
 2007 04  611280.
 2007 05  461341.
 2007 06  891356·
 2007 07  951284·
 2007 08  781266·
 2007 09  131246·
 2007 10  181165·
 2007 11  461208·
 2007 12  201302.
 2008 01 811182.
 2008 02 661197·
 2008 03 61236·
 2008 04 571258.
 2008 05 491179·
 2008 06 651144·
 2008 07 381135·
 2008 08 831079·
 2008 09 431120·
 2008 10 721162·
 2008 11 311160·
 2008 12 171144.
 2009 01  131121·
 2009 02  691133.
 2009 03  971098·
 2009 04  31048·
 2009 05  351056·
 2009 06  621074.
 2009 07  741193·
 2009 08  101162.
 2009 09  81090.
 2009 10  821021·
 2009 11  251021.
 2009 12  331073·
 2010 01 591120.
 2010 02 871180·
 2010 03 381178·
 2010 04 901170·
 2010 05 371154·
 2010 06 581101·
 2010 07 251137·
 2010 08 271030·
 2010 09 181057.
 2010 10 21050.
 2010 11 261026·
 2010 12 111052.
 2011 01  31044·
 2011 02  501094·
 2011 03  11115·
 2011 04  371157.
 2011 05  171142·
 2011 06  591171.
 2011 07  411128·
 2011 08  241126.
 2011 09  101074·
 2011 10  111166.
 2011 11  561142·
 2011 12  171106·
 2012 01 571136·
 2012 02 111061·
 2012 03 861059·
 2012 04 841066·
 2012 05 601069.
 2012 06 931066·
 2012 07 921068.
 2012 08 191131.
 2012 09 421145·
 2012 10 121116·
 2012 11 641175·
 2012 12 431138·
 2013 01  561087·
 2013 02  511131·
 2013 03  131176·
 2013 04  981133·
 2013 05  761135·
 2013 06  151126.
 2013 07  791069·
 2013 08  541106.
 2013 09  21111.
 2013 10  371058·
 2013 11  231134.
 2013 12  51111·
 2014 01 611149·
 2014 02 731200.
 2014 03 331265·
 2014 04 711256.
 2014 05 21236.
 2014 06 41204·
 2014 07 231185.
 2014 08 951159.
 2014 09 01030·
 2014 10 38986·
 2014 11 301076.
 2014 12 471119·
 2015 01  571172·
 2015 02  61271·
 2015 03  181266.
 2015 04  201306.
 2015 05  971285.
 2015 06  641268·
 2015 07  731216·
 2015 08  341160·
 2015 09  711182·
 2015 10  951109·
 2015 11  101165·
 2015 12  331239·
 2016 01 541162.
 2016 02 51219·
 2016 03 651263·
 2016 04 871378.
 2016 05 471420·
 2016 06 251417·
 2016 07 21347.
 2016 08 881208.
 2016 09 761168.
 2016 10 131097·
 2016 11 91149.
 2016 12 571050.
 2017 01  891220.
 2017 02  501250·
 2017 03  981229.
 2017 04  381330·
 2017 05  641383·
 2017 06  421334.
 2017 07  81312·
 2017 08  991286.
 2017 09  01190·


 2017 10  211181.
 2017 11  11221.
 2017 12  351266·
 2018 01 221308.
 2018 02 431296·
 2018 03 661298.
 2018 04 651313.
 2018 05 821381.
 2018 06 921310.
 2018 07 141297·
 2018 08 341249·
 2018 09 531254·
 2018 10 721260·
 2018 11 851324.
 2018 12 91363.
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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: Employed: Wage and salary workers, Real estate and rental and leasing, 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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