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 Series Title: Employment: Nonagriculture Private wage and salary workers in Wholesale and retail trade industry, Men: 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 9610226·
 2000 02 610218.
 2000 03 8010186.
 2000 04 8110180·
 2000 05 010036.
 2000 06 299988.
 2000 07 5910219.
 2000 08 1610300.
 2000 09 210234·
 2000 10 8010310.
 2000 11 7110063·
 2000 12 8010257.
 2001 01  529963.
 2001 02  449998·
 2001 03  2810128·
 2001 04  199991.
 2001 05  259985·
 2001 06  2510164.
 2001 07  6710025.
 2001 08  110173·
 2001 09  2210163.
 2001 10  5610399·
 2001 11  5310219·
 2001 12  2010061.
 2002 01 689717.
 2002 02 939691·
 2002 03 729836·
 2002 04 959838.
 2002 05 1410201.
 2002 06 1810366·
 2002 07 3810536·
 2002 08 7110655·
 2002 09 3410339·
 2002 10 3710253.
 2002 11 8810210.
 2002 12 1710385·
 2003 01  3010292.
 2003 02  8310644.
 2003 03  8610517·
 2003 04  2710419·
 2003 05  2710477·
 2003 06  1210689.
 2003 07  1910968·
 2003 08  2010992·
 2003 09  7510898·
 2003 10  510833·
 2003 11  011026.
 2003 12  4011229·
 2004 01 4911123·
 2004 02 6910974.
 2004 03 6810704·
 2004 04 5710799.
 2004 05 5010804·
 2004 06 3610840.
 2004 07 8411154·
 2004 08 6310838·
 2004 09 310732.
 2004 10 6310934·
 2004 11 3711097.
 2004 12 8011096·
 2005 01  5910910·
 2005 02  3011195·
 2005 03  4011122.
 2005 04  5011199.
 2005 05  9311053.
 2005 06  4610855.
 2005 07  3011228·
 2005 08  4311313·
 2005 09  611215·
 2005 10  4011196·
 2005 11  7111232.
 2005 12  5311199·
 2006 01 2211186.
 2006 02 7011131·
 2006 03 5011083·
 2006 04 011229.
 2006 05 9311213·
 2006 06 1911117·
 2006 07 8111010·
 2006 08 2610952·
 2006 09 9311006·
 2006 10 9111050.
 2006 11 111227.
 2006 12 211078·
 2007 01  2310999·
 2007 02  1910713·
 2007 03  7310737·
 2007 04  2211093·
 2007 05  910860.
 2007 06  6011094·
 2007 07  8510931·
 2007 08  410631.
 2007 09  010547.
 2007 10  9510853·
 2007 11  5010932·
 2007 12  9310927.
 2008 01 7310816.
 2008 02 3010557.
 2008 03 510693.
 2008 04 5810835.
 2008 05 2710687·
 2008 06 9910588.
 2008 07 1410510·
 2008 08 9410544·
 2008 09 8810664.
 2008 10 5610833·
 2008 11 6510740.
 2008 12 1810615·
 2009 01  710161·
 2009 02  8410217.
 2009 03  7010305·
 2009 04  7610258·
 2009 05  5810350·
 2009 06  8910259.
 2009 07  6810285.
 2009 08  3710185·
 2009 09  429942.
 2009 10  410052·
 2009 11  2010077·
 2009 12  949972·
 2010 01 859953.
 2010 02 849984·
 2010 03 1610098·
 2010 04 689971.
 2010 05 3710062·
 2010 06 1110223.
 2010 07 6810119·
 2010 08 110261.
 2010 09 7310228.
 2010 10 9210201·
 2010 11 1310610.
 2010 12 6310503.
 2011 01  9410335.
 2011 02  5910441.
 2011 03  1610209.
 2011 04  4910104.
 2011 05  2510225.
 2011 06  6810185·
 2011 07  6310316.
 2011 08  7710115·
 2011 09  1610263.
 2011 10  110531·
 2011 11  6710520.
 2011 12  9110560.
 2012 01 4310332.
 2012 02 6510137·
 2012 03 6710374.
 2012 04 6110479.
 2012 05 710400.
 2012 06 9010674.
 2012 07 2610691.
 2012 08 8110573.
 2012 09 3210512·
 2012 10 3510500·
 2012 11 3010390·
 2012 12 7110488·
 2013 01  6910481.
 2013 02  7910201.
 2013 03  9410188.
 2013 04  7310266.
 2013 05  9410164.
 2013 06  3110380·
 2013 07  5510530.
 2013 08  5710575·
 2013 09  610440·
 2013 10  2210400.
 2013 11  7510555.
 2013 12  1810441.
 2014 01 3210335.
 2014 02 810318.
 2014 03 4410486.
 2014 04 7410624.
 2014 05 2110465.
 2014 06 7110696.
 2014 07 7310900·
 2014 08 7010481·
 2014 09 5010495·
 2014 10 1710653·
 2014 11 010841·
 2014 12 7510997·
 2015 01  1710780·
 2015 02  7910897·
 2015 03  8910730.
 2015 04  8310864·
 2015 05  5010742.
 2015 06  1310594·
 2015 07  2810725.
 2015 08  1310600·
 2015 09  9710459·
 2015 10  010467.
 2015 11  2810528·
 2015 12  910769·
 2016 01 3610971.
 2016 02 4710992.
 2016 03 2910684.
 2016 04 4110367·
 2016 05 6510337·
 2016 06 8610269·
 2016 07 9310632·
 2016 08 210612.
 2016 09 1010517.
 2016 10 7410855·
 2016 11 810868·
 2016 12 1110891·
 2017 01  2211056.
 2017 02  9210700.
 2017 03  8610750·
 2017 04  1410661.
 2017 05  7710306·
 2017 06  4610521.
 2017 07  6710717.
 2017 08  7810792.


 2017 09  7410960.
 2017 10  6910559·
 2017 11  1110665.
 2017 12  9910625·
 2018 01 3810620.
 2018 02 1710633.
 2018 03 910631.
 2018 04 9510528·
 2018 05 2110389.
 2018 06 7210749·
 2018 07 7110862.
 2018 08 1010876.
 2018 09 9810851·
 2018 10 4010935.
 2018 11 3710899·
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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 Wholesale and retail trade 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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