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 Series Title: Employed: Wholesale trade, Hispanic or Latino: 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 33530.
 2000 02 65595·
 2000 03 12552·
 2000 04 95572·
 2000 05 61608·
 2000 06 56589·
 2000 07 31609·
 2000 08 65607.
 2000 09 19640.
 2000 10 9558·
 2000 11 14538.
 2000 12 96526.
 2001 01  55463.
 2001 02  5608·
 2001 03  73588.
 2001 04  33557·
 2001 05  46535·
 2001 06  49508·
 2001 07  47496·
 2001 08  43484.
 2001 09  93509.
 2001 10  75544·
 2001 11  97540.
 2001 12  23542.
 2002 01 19536·
 2002 02 38488·
 2002 03 13475·
 2002 04 90528·
 2002 05 77549.
 2002 06 20528.
 2002 07 6600.
 2002 08 89601·
 2002 09 40609.
 2002 10 28608.
 2002 11 15579.
 2002 12 89563.
 2003 01  11528·
 2003 02  93540·
 2003 03  3552·
 2003 04  84512·
 2003 05  13575·
 2003 06  73631.
 2003 07  57601.
 2003 08  93565.
 2003 09  97649.
 2003 10  48598·
 2003 11  91634·
 2003 12  61632.
 2004 01 39604·
 2004 02 26560.
 2004 03 42570.
 2004 04 56617·
 2004 05 40611.
 2004 06 37705.
 2004 07 73691·
 2004 08 74614·
 2004 09 24613·
 2004 10 40562.
 2004 11 72575·
 2004 12 31626.
 2005 01  42553.
 2005 02  14563·
 2005 03  52587·
 2005 04  74614.
 2005 05  69627.
 2005 06  68626.
 2005 07  51649·
 2005 08  71637·
 2005 09  6664·
 2005 10  32702.
 2005 11  32660·
 2005 12  17661·
 2006 01 77613·
 2006 02 63577.
 2006 03 83558·
 2006 04 30586.
 2006 05 35640·
 2006 06 44599·
 2006 07 16616·
 2006 08 54638.
 2006 09 53644.
 2006 10 79670.
 2006 11 69639.
 2006 12 59633·
 2007 01  33644·
 2007 02  2603.
 2007 03  6566.
 2007 04  39656.
 2007 05  99599.
 2007 06  69638·
 2007 07  14698.
 2007 08  13646.
 2007 09  2636·
 2007 10  61589·
 2007 11  7646.
 2007 12  25647·
 2008 01 18618.
 2008 02 85599.
 2008 03 21633·
 2008 04 44640·
 2008 05 46652.
 2008 06 73575.
 2008 07 20604·
 2008 08 64533.
 2008 09 13581·
 2008 10 81562.
 2008 11 92519.
 2008 12 5547.
 2009 01  68506·
 2009 02  91527·
 2009 03  49502·
 2009 04  11514.
 2009 05  88571·
 2009 06  10586.
 2009 07  31615·
 2009 08  51620·
 2009 09  71600.
 2009 10  69557.
 2009 11  98553.
 2009 12  18556.
 2010 01 45546.
 2010 02 25497.
 2010 03 40523·
 2010 04 33574·
 2010 05 58579.
 2010 06 59618·
 2010 07 69576·
 2010 08 39566·
 2010 09 88568.
 2010 10 79570.
 2010 11 24604·
 2010 12 5549.
 2011 01  33611.
 2011 02  15596.
 2011 03  66634.
 2011 04  26629·
 2011 05  19629·
 2011 06  25600.
 2011 07  84653·
 2011 08  21572·
 2011 09  97576·
 2011 10  90587.
 2011 11  91507.
 2011 12  33533·
 2012 01 43537·
 2012 02 17491.
 2012 03 25540.
 2012 04 32560·
 2012 05 56613.
 2012 06 37645·
 2012 07 48708·
 2012 08 13651·
 2012 09 61714·
 2012 10 8657.
 2012 11 49680·
 2012 12 93629·
 2013 01  10594.
 2013 02  10629·
 2013 03  40591·
 2013 04  18575.
 2013 05  78568·
 2013 06  50547.
 2013 07  60575.
 2013 08  57562·
 2013 09  65590·
 2013 10  60599·
 2013 11  70571.
 2013 12  3546.
 2014 01 96605·
 2014 02 97581.
 2014 03 60536.
 2014 04 75542·
 2014 05 22489.
 2014 06 42463·
 2014 07 41551.
 2014 08 19551.
 2014 09 19604.
 2014 10 2619.
 2014 11 52703.
 2014 12 3679·
 2015 01  86668·
 2015 02  8603·
 2015 03  56540·
 2015 04  21576·
 2015 05  49604.
 2015 06  18610.
 2015 07  41589·
 2015 08  93553.
 2015 09  58612·
 2015 10  12646·
 2015 11  19679.
 2015 12  62681·
 2016 01 89683·
 2016 02 98709.
 2016 03 29724·
 2016 04 97590·
 2016 05 43624·
 2016 06 7553·
 2016 07 32556.
 2016 08 93610.
 2016 09 44668.
 2016 10 95672·
 2016 11 18691.
 2016 12 70624.
 2017 01  43633.
 2017 02  45578.
 2017 03  99609.
 2017 04  70617.
 2017 05  15600.
 2017 06  63601·
 2017 07  13579·
 2017 08  63601·
 2017 09  61623·
 2017 10  81564.
 2017 11  23641.
 2017 12  44651.


 2018 01 7688·
 2018 02 54721.
 2018 03 16761.
 2018 04 32719.
 2018 05 1659·
 2018 06 66736.
 2018 07 6742·
 2018 08 69699.
 2018 09 21711.
 2018 10 23704.
 2018 11 31626·
 2018 12 27703.
 2019 01  66684.
 2019 02  55602·
 2019 03  53590.
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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 trade, Hispanic or Latino: 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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