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 Series Title: Men, employed government 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
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 2012 04 4831·
 2012 03 1042.
 2012 02 3534·
 2012 01 2541·
 2011 12  750·
 2011 11  1054.
 2011 10  6467·
 2011 09  3152·
 2011 08  5259.
 2011 07  2654·
 2011 06  1263·
 2011 05  5468·
 2011 04  3251·
 2011 03  4157·
 2011 02  9373·
 2011 01  3859·
 2010 12 2344.
 2010 11 6241·
 2010 10 4439.
 2010 09 5359.
 2010 08 2552·
 2010 07 2041·
 2010 06 2953·
 2010 05 9345·
 2010 04 6452·
 2010 03 7268·
 2010 02 3463·
 2010 01 7774.
 2009 12  9059·
 2009 11  9950.
 2009 10  7445.
 2009 09  4944·
 2009 08  7831·
 2009 07  941·
 2009 06  8639·
 2009 05  7939.
 2009 04  2946.
 2009 03  3260.
 2009 02  3344.
 2009 01  5942.
 2008 12 6829.
 2008 11 2528·
 2008 10 246·
 2008 09 1136·
 2008 08 4636·
 2008 07 7035.
 2008 06 834·
 2008 05 7752·
 2008 04 3840.
 2008 03 7433.
 2008 02 8642·
 2008 01 2631·
 2007 12  4531.
 2007 11  6835·
 2007 10  235·
 2007 09  5438·
 2007 08  9170.
 2007 07  966·
 2007 06  4155.
 2007 05  7952·
 2007 04  2735.
 2007 03  7926.
 2007 02  1835·
 2007 01  4543·
 2006 12 2954·
 2006 11 8467.
 2006 10 7057·
 2006 09 2247.
 2006 08 9771.
 2006 07 5569.
 2006 06 6057·
 2006 05 355·
 2006 04 5645.
 2006 03 5138·
 2006 02 7648.
 2006 01 751.
 2005 12  5743·
 2005 11  5147.
 2005 10  3131.
 2005 09  8044.
 2005 08  7556.
 2005 07  6348·
 2005 06  6249.
 2005 05  8954·
 2005 04  1057.
 2005 03  1861.
 2005 02  3360.
 2005 01  3039.
 2004 12 8955·
 2004 11 7450.
 2004 10 3137.
 2004 09 2039·
 2004 08 6044.
 2004 07 1140·
 2004 06 7045.
 2004 05 547·
 2004 04 131.
 2004 03 3650·
 2004 02 8745.
 2004 01 5447·
 2003 12  1051·
 2003 11  8153·
 2003 10  4540·
 2003 09  6033.
 2003 08  1436·
 2003 07  341·
 2003 06  3356·
 2003 05  4353·
 2003 04  6356.
 2003 03  8335·
 2003 02  6240.
 2003 01  4751·
 2002 12 3260·
 2002 11 2864.
 2002 10 7161.
 2002 09 4157·
 2002 08 2256·
 2002 07 7055.
 2002 06 2247.
 2002 05 1951.
 2002 04 5736.
 2002 03 6529.
 2002 02 541.
 2002 01 138.
 2001 12  8942·
 2001 11  9466·
 2001 10  3164·
 2001 09  3054.
 2001 08  9365.
 2001 07  6549.
 2001 06  3849.
 2001 05  7649·
 2001 04  6947·
 2001 03  936·
 2001 02  8953.
 2001 01  3250·
 2000 12 4361·
 2000 11 8367·
 2000 10 7361·
 2000 09 1979.
 2000 08 6573.
 2000 07 6868·
 2000 06 157·
 2000 05 7958.
 2000 04 1061.
 2000 03 7173·
 2000 02 1378.
 2000 01 8359.
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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: Men, employed government 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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