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 Series Title: Employed: Real estate and rental and leasing, Asian: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Yearly Chart  |  Excel file  |  Self-updating Excel file
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 2000 01 7884.
 2000 02 8893·
 2000 03 44104.
 2000 04 398·
 2000 05 51110·
 2000 06 71130.
 2000 07 5193.
 2000 08 8109·
 2000 09 4089·
 2000 10 3102·
 2000 11 10112.
 2000 12 62117.
 2001 01  96119·
 2001 02  64104.
 2001 03  32129.
 2001 04  8126·
 2001 05  94113.
 2001 06  62117.
 2001 07  56100.
 2001 08  1683.
 2001 09  3572·
 2001 10  2984.
 2001 11  4489·
 2001 12  8183·
 2002 01 43124.
 2002 02 2196.
 2002 03 85103.
 2002 04 20104·
 2002 05 7065.
 2002 06 19102·
 2002 07 9265.
 2002 08 7984.
 2002 09 9187.
 2002 10 3168.
 2002 11 173.
 2002 12 2684·
 2003 01  578·
 2003 02  8895·
 2003 03  7785·
 2003 04  5777·
 2003 05  3972.
 2003 06  4674·
 2003 07  774·
 2003 08  8894.
 2003 09  4376·
 2003 10  8770.
 2003 11  479.
 2003 12  6695.
 2004 01 9283·
 2004 02 19117·
 2004 03 5103.
 2004 04 5998.
 2004 05 8794·
 2004 06 7267.
 2004 07 7572.
 2004 08 6165·
 2004 09 5281.
 2004 10 389.
 2004 11 99102·
 2004 12 91111.
 2005 01  40123.
 2005 02  93109·
 2005 03  93118.
 2005 04  94129.
 2005 05  24111·
 2005 06  51103·
 2005 07  92103·
 2005 08  3995·
 2005 09  572·
 2005 10  687.
 2005 11  6193·
 2005 12  19111·
 2006 01 9130.
 2006 02 16129·
 2006 03 88154.
 2006 04 54160·
 2006 05 85170.
 2006 06 62151·
 2006 07 84135·
 2006 08 8997.
 2006 09 1097.
 2006 10 52117.
 2006 11 88115.
 2006 12 91143.
 2007 01  84164.
 2007 02  16154.
 2007 03  63173·
 2007 04  56145·
 2007 05  3299·
 2007 06  11127.
 2007 07  97115·
 2007 08  2149·
 2007 09  5142·
 2007 10  20139.
 2007 11  2134.
 2007 12  74125·
 2008 01 77114.
 2008 02 47123.
 2008 03 17120.
 2008 04 41115.
 2008 05 50117.
 2008 06 2688·
 2008 07 477.
 2008 08 9682.
 2008 09 4986.
 2008 10 13109.
 2008 11 51112·
 2008 12 60110.
 2009 01  2395.
 2009 02  90115·
 2009 03  72120·
 2009 04  76122·
 2009 05  50110·
 2009 06  6299.
 2009 07  4105·
 2009 08  1397·
 2009 09  2896·
 2009 10  6285·
 2009 11  982.
 2009 12  6585.
 2010 01 83112·
 2010 02 4789.
 2010 03 7788·
 2010 04 53103.
 2010 05 6686.
 2010 06 98101.
 2010 07 19107.
 2010 08 18105·
 2010 09 5290·
 2010 10 2192·
 2010 11 74106·
 2010 12 3296.
 2011 01  41109·
 2011 02  49142.
 2011 03  4104.
 2011 04  88127·
 2011 05  60117.
 2011 06  37103.
 2011 07  98109·
 2011 08  5121·
 2011 09  57101.
 2011 10  6999·
 2011 11  68101.
 2011 12  2786.
 2012 01 989.
 2012 02 49104·
 2012 03 53102·
 2012 04 24132·
 2012 05 17145·
 2012 06 11125·
 2012 07 14131·
 2012 08 89138·
 2012 09 4112.
 2012 10 1097.
 2012 11 40100.
 2012 12 42102·
 2013 01  2297.
 2013 02  28106.
 2013 03  45120.
 2013 04  27166·
 2013 05  47138.
 2013 06  72119·
 2013 07  65117.
 2013 08  1387.
 2013 09  7891.
 2013 10  7385·
 2013 11  6393·
 2013 12  9499·
 2014 01 4191.
 2014 02 89112·
 2014 03 28109.
 2014 04 89120·
 2014 05 87105·
 2014 06 0118·
 2014 07 7393·
 2014 08 4391.
 2014 09 90112·
 2014 10 13117·
 2014 11 35123.
 2014 12 24104·
 2015 01  51106·
 2015 02  6196·
 2015 03  77121.
 2015 04  27114·
 2015 05  96124·
 2015 06  99143.
 2015 07  87109·
 2015 08  71150.
 2015 09  75140·
 2015 10  10130.
 2015 11  78141.
 2015 12  0140·
 2016 01 63136.
 2016 02 99136·
 2016 03 89103·
 2016 04 83110.
 2016 05 61121·
 2016 06 99147·
 2016 07 80161·
 2016 08 15169.
 2016 09 94115·
 2016 10 67119.
 2016 11 42127·
 2016 12 13117·
 2017 01  12143·
 2017 02  83136.
 2017 03  86145.
 2017 04  24145·
 2017 05  91133·
 2017 06  54140.
 2017 07  50136.


 2017 08  14143.
 2017 09  32115·
 2017 10  13125·
 2017 11  98124.
 2017 12  80114·
 2018 01 59135.
 2018 02 16160·
 2018 03 17226·
 2018 04 40217·
 2018 05 23207.
 2018 06 44206.
 2018 07 20177·
 2018 08 38163.
 2018 09 0158·
 2018 10 4139·
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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: Real estate and rental and leasing, Asian: 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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