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 Series Title: Employed: Durable goods manufacturing, 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 731349.
 2000 02 241336·
 2000 03 841316·
 2000 04 61415.
 2000 05 661354.
 2000 06 441358·
 2000 07 211385.
 2000 08 71326·
 2000 09 941387.
 2000 10 321413·
 2000 11 281394.
 2000 12 761353.
 2001 01  81353.
 2001 02  681345·
 2001 03  171366.
 2001 04  571425·
 2001 05  831332·
 2001 06  601308.
 2001 07  271352·
 2001 08  181306.
 2001 09  181368·
 2001 10  391353.
 2001 11  201281.
 2001 12  541275·
 2002 01 411180·
 2002 02 621139.
 2002 03 841199.
 2002 04 841179.
 2002 05 01172.
 2002 06 111261.
 2002 07 331288·
 2002 08 521272·
 2002 09 721213·
 2002 10 911229·
 2002 11 31258.
 2002 12 281273.
 2003 01  571349·
 2003 02  351405.
 2003 03  591307·
 2003 04  51249·
 2003 05  801100·
 2003 06  991145.
 2003 07  871184.
 2003 08  21238·
 2003 09  911186·
 2003 10  661199·
 2003 11  11218·
 2003 12  641194.
 2004 01 671242·
 2004 02 411198·
 2004 03 381124.
 2004 04 601209·
 2004 05 71142·
 2004 06 561158·
 2004 07 621249·
 2004 08 841315.
 2004 09 371289·
 2004 10 681230.
 2004 11 601260·
 2004 12 551174.
 2005 01  71156·
 2005 02  591106·
 2005 03  461131·
 2005 04  171262.
 2005 05  921340.
 2005 06  351368.
 2005 07  561310·
 2005 08  391222.
 2005 09  931312·
 2005 10  281291·
 2005 11  551207·
 2005 12  171236·
 2006 01 361240.
 2006 02 941278·
 2006 03 291433.
 2006 04 671375·
 2006 05 711406.
 2006 06 151327.
 2006 07 921309.
 2006 08 361243.
 2006 09 721248·
 2006 10 981257.
 2006 11 821248.
 2006 12 911274.
 2007 01  411178.
 2007 02  751255.
 2007 03  621278·
 2007 04  281247.
 2007 05  31354·
 2007 06  11232·
 2007 07  191228·
 2007 08  651297·
 2007 09  91310.
 2007 10  591361.
 2007 11  661354·
 2007 12  461310.
 2008 01 321290.
 2008 02 561247·
 2008 03 421203·
 2008 04 411203·
 2008 05 761227·
 2008 06 221307·
 2008 07 91318.
 2008 08 431293·
 2008 09 631237·
 2008 10 151273.
 2008 11 551259.
 2008 12 721263.
 2009 01  451346.
 2009 02  161199.
 2009 03  921233.
 2009 04  721149.
 2009 05  981091·
 2009 06  331115·
 2009 07  601140·
 2009 08  121092·
 2009 09  211138.
 2009 10  951078·
 2009 11  201116.
 2009 12  871095.
 2010 01 411105·
 2010 02 611137.
 2010 03 611043·
 2010 04 141027·
 2010 05 61137.
 2010 06 121146·
 2010 07 951222.
 2010 08 391216.
 2010 09 941223·
 2010 10 541151·
 2010 11 611147·
 2010 12 311191·
 2011 01  31155·
 2011 02  191149.
 2011 03  211002.
 2011 04  841091.
 2011 05  611067·
 2011 06  641112.
 2011 07  631132·
 2011 08  161175.
 2011 09  161193·
 2011 10  701163.
 2011 11  11165·
 2011 12  731274·
 2012 01 451195.
 2012 02 441203.
 2012 03 711094.
 2012 04 231137.
 2012 05 471174·
 2012 06 181172.
 2012 07 371230·
 2012 08 601234·
 2012 09 481164·
 2012 10 481167·
 2012 11 861136.
 2012 12 31163.
 2013 01  01251.
 2013 02  161248·
 2013 03  331224.
 2013 04  971212.
 2013 05  761161·
 2013 06  291208.
 2013 07  141255.
 2013 08  111278.
 2013 09  771342.
 2013 10  171282·
 2013 11  921430·
 2013 12  391370.
 2014 01 291359·
 2014 02 391335·
 2014 03 551207·
 2014 04 01213·
 2014 05 821274.
 2014 06 751342·
 2014 07 171258.
 2014 08 381318.
 2014 09 121367·
 2014 10 321345.
 2014 11 151399·
 2014 12 221475·
 2015 01  181571·
 2015 02  421469.
 2015 03  111383.
 2015 04  471310.
 2015 05  271279·
 2015 06  621363.
 2015 07  951407·
 2015 08  321332.
 2015 09  891300·
 2015 10  721401·
 2015 11  781337.
 2015 12  201365·
 2016 01 781321.
 2016 02 801438.
 2016 03 991453·
 2016 04 811433.
 2016 05 961454·
 2016 06 181401·
 2016 07 201352.
 2016 08 91360.
 2016 09 681338.
 2016 10 411311·
 2016 11 301261·
 2016 12 231318.
 2017 01  441268.
 2017 02  321410.
 2017 03  411421·
 2017 04  681390·
 2017 05  01443.
 2017 06  981384.
 2017 07  921411·
 2017 08  111253.


 2017 09  351317.
 2017 10  691363·
 2017 11  441312.
 2017 12  491329·
 2018 01 771376·
 2018 02 21409·
 2018 03 871439.
 2018 04 991482.
 2018 05 731415·
 2018 06 801345.
 2018 07 321311·
 2018 08 61337.
 2018 09 21352·
 2018 10 91423·
 2018 11 181479.
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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: Durable goods manufacturing, 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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