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 Series Title: Employment: Nonagriculture Private wage and salary workers in Real estate and rental and leasing industry, Men: NSA
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 2000 01 381186·
 2000 02 821196.
 2000 03 81225.
 2000 04 811190.
 2000 05 911134.
 2000 06 281131·
 2000 07 861149·
 2000 08 891127.
 2000 09 411070.
 2000 10 31126·
 2000 11 961029.
 2000 12 271054·
 2001 01  391181·
 2001 02  901163.
 2001 03  511211·
 2001 04  391224.
 2001 05  611242·
 2001 06  941227·
 2001 07  891207·
 2001 08  941136.
 2001 09  61127.
 2001 10  481130.
 2001 11  731125·
 2001 12  871133·
 2002 01 01161.
 2002 02 91160.
 2002 03 911153·
 2002 04 361232.
 2002 05 951194·
 2002 06 581251.
 2002 07 551301.
 2002 08 851207.
 2002 09 641154.
 2002 10 11143·
 2002 11 41199·
 2002 12 51212·
 2003 01  81228.
 2003 02  701185.
 2003 03  01135·
 2003 04  881201.
 2003 05  531260.
 2003 06  221253.
 2003 07  321300.
 2003 08  541308.
 2003 09  491291·
 2003 10  391274·
 2003 11  111338.
 2003 12  481348·
 2004 01 721249.
 2004 02 261265.
 2004 03 771255·
 2004 04 381236·
 2004 05 211287·
 2004 06 171330.
 2004 07 921439.
 2004 08 181307·
 2004 09 231266·
 2004 10 671333·
 2004 11 431232·
 2004 12 81325.
 2005 01  271305.
 2005 02  581393·
 2005 03  451418.
 2005 04  521300·
 2005 05  101327·
 2005 06  961337·
 2005 07  331322.
 2005 08  181358.
 2005 09  711334·
 2005 10  141369·
 2005 11  731311·
 2005 12  21323.
 2006 01 361295·
 2006 02 681305·
 2006 03 511308·
 2006 04 211290·
 2006 05 551279·
 2006 06 401292.
 2006 07 801287.
 2006 08 211328.
 2006 09 31321.
 2006 10 351435·
 2006 11 981387·
 2006 12 711447·
 2007 01  821409.
 2007 02  871328.
 2007 03  681411.
 2007 04  641409.
 2007 05  161403.
 2007 06  511272.
 2007 07  791270.
 2007 08  191372.
 2007 09  561394·
 2007 10  91421.
 2007 11  421385.
 2007 12  821337·
 2008 01 771213·
 2008 02 691237·
 2008 03 961259.
 2008 04 211275·
 2008 05 801334.
 2008 06 601353.
 2008 07 41343.
 2008 08 301367.
 2008 09 891304·
 2008 10 411296·
 2008 11 531302.
 2008 12 281322.
 2009 01  561328.
 2009 02  921318.
 2009 03  561272·
 2009 04  591237·
 2009 05  561255·
 2009 06  211277.
 2009 07  521230·
 2009 08  931267.
 2009 09  891192.
 2009 10  591234.
 2009 11  31189.
 2009 12  241229·
 2010 01 801232·
 2010 02 631215·
 2010 03 971216·
 2010 04 711181·
 2010 05 801125.
 2010 06 131187·
 2010 07 481156.
 2010 08 771122·
 2010 09 651145·
 2010 10 181197.
 2010 11 921202·
 2010 12 131251.
 2011 01  341166·
 2011 02  81190·
 2011 03  921197.
 2011 04  721215·
 2011 05  131125.
 2011 06  411118·
 2011 07  381100·
 2011 08  731151·
 2011 09  531234.
 2011 10  971225.
 2011 11  411341·
 2011 12  611321·
 2012 01 291281·
 2012 02 841290·
 2012 03 391321.
 2012 04 51263.
 2012 05 411293·
 2012 06 331242·
 2012 07 961160.
 2012 08 991187.
 2012 09 141188.
 2012 10 11237·
 2012 11 991278·
 2012 12 611266·
 2013 01  01173·
 2013 02  691185.
 2013 03  611265.
 2013 04  371299.
 2013 05  731352.
 2013 06  441249·
 2013 07  211204·
 2013 08  941277·
 2013 09  341283.
 2013 10  581325·
 2013 11  401343·
 2013 12  291305.
 2014 01 81258·
 2014 02 681230·
 2014 03 61285.
 2014 04 591178·
 2014 05 461209·
 2014 06 541350.
 2014 07 341296.
 2014 08 281369·
 2014 09 231350·
 2014 10 241301.
 2014 11 601306.
 2014 12 61314.
 2015 01  391283.
 2015 02  91250.
 2015 03  471342·
 2015 04  881251.
 2015 05  201318.
 2015 06  661411.
 2015 07  841479·
 2015 08  911447·
 2015 09  161444.
 2015 10  771360.
 2015 11  831274.
 2015 12  611317.
 2016 01 21297·
 2016 02 481291·
 2016 03 831436·
 2016 04 661512·
 2016 05 801444.
 2016 06 111510·
 2016 07 451452·
 2016 08 01395·
 2016 09 741438.
 2016 10 221521·
 2016 11 581481.
 2016 12 831393.
 2017 01  341375.
 2017 02  631477.
 2017 03  351484·
 2017 04  591466.
 2017 05  371441·
 2017 06  411344.
 2017 07  141464.
 2017 08  971436·
 2017 09  821477.


 2017 10  871502·
 2017 11  571399.
 2017 12  911420·
 2018 01 961464·
 2018 02 591417.
 2018 03 531416.
 2018 04 601377·
 2018 05 271369·
 2018 06 371480.
 2018 07 141598·
 2018 08 491465·
 2018 09 521465·
 2018 10 281426·
 2018 11 781340.
 2018 12 261480.
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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: Nonagriculture Private wage and salary workers in Real estate and rental and leasing industry, Men: 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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