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 Series Title: (orig) Employment: Nonagriculture private wage and salary workers in Real estate and rental and leasing: 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 972188.
 2000 02 342206·
 2000 03 162215.
 2000 04 402270.
 2000 05 252224.
 2000 06 942304.
 2000 07 732276.
 2000 08 152248·
 2000 09 572151.
 2000 10 902156.
 2000 11 682044·
 2000 12 272038.
 2001 01  432152·
 2001 02  42202·
 2001 03  142290·
 2001 04  192271.
 2001 05  592404·
 2001 06  422387·
 2001 07  502360.
 2001 08  612289·
 2001 09  52217.
 2001 10  362187.
 2001 11  372203.
 2001 12  462238·
 2002 01 62286.
 2002 02 422259.
 2002 03 652270·
 2002 04 942367.
 2002 05 132402·
 2002 06 432460·
 2002 07 452391.
 2002 08 492270·
 2002 09 12250·
 2002 10 442198.
 2002 11 162272.
 2002 12 802255·
 2003 01  712283·
 2003 02  782284·
 2003 03  412224·
 2003 04  812320.
 2003 05  482381.
 2003 06  12425.
 2003 07  82472.
 2003 08  712434·
 2003 09  822415·
 2003 10  952324.
 2003 11  282417·
 2003 12  952473.
 2004 01 492304.
 2004 02 662385.
 2004 03 412369.
 2004 04 212358·
 2004 05 492453.
 2004 06 462492.
 2004 07 102654·
 2004 08 442486.
 2004 09 72456·
 2004 10 912585.
 2004 11 212430.
 2004 12 832489.
 2005 01  752485·
 2005 02  842575.
 2005 03  882624.
 2005 04  822611.
 2005 05  272526·
 2005 06  312525.
 2005 07  502562.
 2005 08  102613·
 2005 09  632637·
 2005 10  642755.
 2005 11  682676·
 2005 12  612647·
 2006 01 102573.
 2006 02 382584.
 2006 03 302626·
 2006 04 542628.
 2006 05 172641·
 2006 06 372648.
 2006 07 512595.
 2006 08 352573.
 2006 09 592556.
 2006 10 662705·
 2006 11 662687·
 2006 12 702728.
 2007 01  392647.
 2007 02  572589.
 2007 03  402697·
 2007 04  562639·
 2007 05  792688.
 2007 06  672585·
 2007 07  602516.
 2007 08  112590.
 2007 09  322588·
 2007 10  782521.
 2007 11  402535.
 2007 12  792588.
 2008 01 732356.
 2008 02 952398.
 2008 03 162448·
 2008 04 292484.
 2008 05 12469.
 2008 06 512455.
 2008 07 522442·
 2008 08 552408·
 2008 09 422387·
 2008 10 32420.
 2008 11 362425·
 2008 12 772431·
 2009 01  472422·
 2009 02  312436.
 2009 03  812342·
 2009 04  392237.
 2009 05  912245·
 2009 06  432290.
 2009 07  242380.
 2009 08  92382·
 2009 09  742245·
 2009 10  712220·
 2009 11  292173.
 2009 12  832275·
 2010 01 222316·
 2010 02 702365·
 2010 03 832367.
 2010 04 782324·
 2010 05 852245·
 2010 06 232238·
 2010 07 992241·
 2010 08 402098.
 2010 09 392137.
 2010 10 362207·
 2010 11 162161.
 2010 12 372251·
 2011 01  842157.
 2011 02  412214·
 2011 03  952263·
 2011 04  642314.
 2011 05  452198.
 2011 06  942230·
 2011 07  252178·
 2011 08  392231.
 2011 09  732256.
 2011 10  782353.
 2011 11  202451.
 2011 12  72383·
 2012 01 432365.
 2012 02 982277·
 2012 03 152304.
 2012 04 382271·
 2012 05 552292·
 2012 06 862264.
 2012 07 762171·
 2012 08 242263·
 2012 09 362289.
 2012 10 02307·
 2012 11 892403·
 2012 12 852362.
 2013 01  342212.
 2013 02  202270·
 2013 03  672381·
 2013 04  662363·
 2013 05  272423.
 2013 06  542325·
 2013 07  482218·
 2013 08  352353·
 2013 09  132370·
 2013 10  322364.
 2013 11  962447.
 2013 12  872386·
 2014 01 192372·
 2014 02 122389·
 2014 03 982510.
 2014 04 412392.
 2014 05 952396.
 2014 06 762501·
 2014 07 662424·
 2014 08 412475·
 2014 09 162337·
 2014 10 292249·
 2014 11 402348.
 2014 12 552404·
 2015 01  822427.
 2015 02  42497.
 2015 03  812587.
 2015 04  792529.
 2015 05  202568.
 2015 06  572645·
 2015 07  782659·
 2015 08  312578·
 2015 09  792604·
 2015 10  692435·
 2015 11  432396.
 2015 12  562503.
 2016 01 352406·
 2016 02 482479.
 2016 03 142648·
 2016 04 232854.
 2016 05 882832·
 2016 06 262897.
 2016 07 552772·
 2016 08 252567·
 2016 09 632563.
 2016 10 582583.
 2016 11 532602·
 2016 12 822406·
 2017 01  122551.
 2017 02  262680·
 2017 03  212675.
 2017 04  382773·
 2017 05  92799.
 2017 06  372653.
 2017 07  972754.
 2017 08  622684.
 2017 09  552634.


 2017 10  232642·
 2017 11  442582.
 2017 12  492649.
 2018 01 752738·
 2018 02 402677.
 2018 03 502684·
 2018 04 172657·
 2018 05 192718.
 2018 06 702753.
 2018 07 272846.
 2018 08 112667.
 2018 09 632677·
 2018 10 202643.
 2018 11 142633·
 2018 12 02817·
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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: (orig) Employment: Nonagriculture private wage and salary workers in Real estate and rental and leasing: 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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