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 Series Title: Employed: Wholesale and retail trade, White: 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 3417406.
 2000 02 317088·
 2000 03 2516984·
 2000 04 2017136·
 2000 05 3516847·
 2000 06 1716799.
 2000 07 1617239.
 2000 08 1117486.
 2000 09 6417246.
 2000 10 9117482.
 2000 11 7117145.
 2000 12 6417248.
 2001 01  7316724.
 2001 02  916811·
 2001 03  216903·
 2001 04  2316754·
 2001 05  3616785·
 2001 06  7516867.
 2001 07  4717014.
 2001 08  5517011·
 2001 09  5417026·
 2001 10  2217003·
 2001 11  6916843.
 2001 12  5617014.
 2002 01 5216443.
 2002 02 716297·
 2002 03 5716516.
 2002 04 4516501.
 2002 05 8216965·
 2002 06 1117347.
 2002 07 2217397·
 2002 08 6617322.
 2002 09 1716966·
 2002 10 4117022·
 2002 11 317244·
 2002 12 8817578.
 2003 01  5917211.
 2003 02  2917287.
 2003 03  6217116·
 2003 04  517204.
 2003 05  3317087·
 2003 06  3017285.
 2003 07  8817650·
 2003 08  3617584.
 2003 09  9017558.
 2003 10  2717711.
 2003 11  9418308·
 2003 12  2618393·
 2004 01 417877·
 2004 02 2717817.
 2004 03 1717092·
 2004 04 4317074.
 2004 05 7617141.
 2004 06 6017073.
 2004 07 2017798·
 2004 08 8217655.
 2004 09 3217475.
 2004 10 8417865·
 2004 11 9117975.
 2004 12 6218049·
 2005 01  2117818·
 2005 02  8117979·
 2005 03  4317745.
 2005 04  2717907.
 2005 05  2017883.
 2005 06  5617516·
 2005 07  1418130.
 2005 08  4618286·
 2005 09  2918113.
 2005 10  4218267.
 2005 11  6718473.
 2005 12  1318561.
 2006 01 7318265.
 2006 02 9617934·
 2006 03 8917999.
 2006 04 4818043.
 2006 05 217981·
 2006 06 9818114·
 2006 07 9418005·
 2006 08 9417746·
 2006 09 9217638.
 2006 10 5517622·
 2006 11 2018103.
 2006 12 2118063·
 2007 01  4417735.
 2007 02  017345·
 2007 03  2817338.
 2007 04  2217564·
 2007 05  8217334.
 2007 06  8817916·
 2007 07  817771·
 2007 08  1817088.
 2007 09  5716997·
 2007 10  217130.
 2007 11  7217403.
 2007 12  5217601.
 2008 01 4517401.
 2008 02 4817280·
 2008 03 5917294.
 2008 04 9317314·
 2008 05 4517121·
 2008 06 5817079.
 2008 07 2916991.
 2008 08 3616951.
 2008 09 8317150·
 2008 10 8817124·
 2008 11 7316973·
 2008 12 9917160·
 2009 01  1116470.
 2009 02  2016711·
 2009 03  316622·
 2009 04  2616368.
 2009 05  216425.
 2009 06  6116559.
 2009 07  5616443·
 2009 08  8816385.
 2009 09  5716090·
 2009 10  4216000.
 2009 11  9516290·
 2009 12  7716471·
 2010 01 316430.
 2010 02 1916454·
 2010 03 916570·
 2010 04 1416581.
 2010 05 8816203.
 2010 06 7616276·
 2010 07 1016131·
 2010 08 4216206.
 2010 09 8916312·
 2010 10 1716332.
 2010 11 3616719·
 2010 12 3016725.
 2011 01  616638·
 2011 02  7616469·
 2011 03  5016326.
 2011 04  7216289.
 2011 05  6516260·
 2011 06  816078.
 2011 07  4116232.
 2011 08  8916189.
 2011 09  1516430·
 2011 10  9416574·
 2011 11  1916644·
 2011 12  2316576·
 2012 01 3216070·
 2012 02 4315954·
 2012 03 2516195·
 2012 04 4416037.
 2012 05 1716061·
 2012 06 8516249·
 2012 07 2016317.
 2012 08 4616128·
 2012 09 9416160.
 2012 10 7716310·
 2012 11 9316379·
 2012 12 4916306.
 2013 01  1516055·
 2013 02  115641·
 2013 03  5615632·
 2013 04  9615932·
 2013 05  5516039.
 2013 06  6316017.
 2013 07  4716127.
 2013 08  5615954·
 2013 09  1315753.
 2013 10  9515791·
 2013 11  3016038·
 2013 12  2416040·
 2014 01 1715872·
 2014 02 5416038.
 2014 03 9116204.
 2014 04 1916343·
 2014 05 1516035.
 2014 06 2116122.
 2014 07 4416292.
 2014 08 8415860·
 2014 09 8316056.
 2014 10 316354·
 2014 11 2816689.
 2014 12 9016873·
 2015 01  2216435·
 2015 02  3116459.
 2015 03  316227·
 2015 04  3016050.
 2015 05  5716178.
 2015 06  6216105·
 2015 07  6016019.
 2015 08  2316127·
 2015 09  3816058.
 2015 10  7816101·
 2015 11  1016323·
 2015 12  1416273·
 2016 01 4116160·
 2016 02 8616279·
 2016 03 9116162.
 2016 04 7115655.
 2016 05 6615693.
 2016 06 1715721·
 2016 07 6716109.
 2016 08 9016118·
 2016 09 3915965·
 2016 10 2716144·
 2016 11 2516361·
 2016 12 8816244.
 2017 01  1016423·
 2017 02  9916240.
 2017 03  7816043.
 2017 04  1015885·
 2017 05  5415418·
 2017 06  3915596·
 2017 07  6315988·
 2017 08  2515869·
 2017 09  7216296.
 2017 10  7816008·
 2017 11  4516206.


 2017 12  2816236.
 2018 01 9015842·
 2018 02 7415910.
 2018 03 1015887.
 2018 04 3715630.
 2018 05 5615581·
 2018 06 816064.
 2018 07 7216067.
 2018 08 9716062.
 2018 09 4815937.
 2018 10 8616114.
 2018 11 6916208.
 2018 12 7616067·
 2019 01  6515530.
 2019 02  4015417.
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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: Wholesale and retail trade, White: 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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Sites of Interest: Conerly Consulting: Economics for Business Decisions *

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