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 Series Title: Employment Level: Production Occupations, Mexican: 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 571456·
 2000 02 811511·
 2000 03 121504·
 2000 04 191467·
 2000 05 991478.
 2000 06 491476·
 2000 07 691495·
 2000 08 891442·
 2000 09 191521.
 2000 10 271560.
 2000 11 401563.
 2000 12 711576·
 2001 01  691561.
 2001 02  991595·
 2001 03  381529·
 2001 04  81513.
 2001 05  241476.
 2001 06  691399·
 2001 07  01412.
 2001 08  701403·
 2001 09  831409.
 2001 10  701388.
 2001 11  881437·
 2001 12  501363.
 2002 01 731333.
 2002 02 591345.
 2002 03 921432·
 2002 04 681396.
 2002 05 441454.
 2002 06 171366·
 2002 07 241474·
 2002 08 681505.
 2002 09 711453.
 2002 10 511432·
 2002 11 211394·
 2002 12 181316·
 2003 01  541326·
 2003 02  921425·
 2003 03  471382.
 2003 04  141463·
 2003 05  201410.
 2003 06  971329.
 2003 07  891357·
 2003 08  741452.
 2003 09  181348.
 2003 10  481454.
 2003 11  611445.
 2003 12  431313·
 2004 01 231345·
 2004 02 521305.
 2004 03 11304.
 2004 04 891499·
 2004 05 371415.
 2004 06 391390.
 2004 07 701416·
 2004 08 71395.
 2004 09 841325·
 2004 10 671261.
 2004 11 581265.
 2004 12 161108·
 2005 01  151186.
 2005 02  181175·
 2005 03  761212·
 2005 04  591455·
 2005 05  51533·
 2005 06  971526.
 2005 07  641391·
 2005 08  71347·
 2005 09  561299·
 2005 10  371288·
 2005 11  831280.
 2005 12  531239.
 2006 01 911275·
 2006 02 941327·
 2006 03 221496.
 2006 04 171476·
 2006 05 621408.
 2006 06 501441.
 2006 07 931387·
 2006 08 421319.
 2006 09 431286·
 2006 10 121335·
 2006 11 351283·
 2006 12 981305.
 2007 01  361303.
 2007 02  101327.
 2007 03  101406·
 2007 04  781416.
 2007 05  651424.
 2007 06  31306·
 2007 07  61385.
 2007 08  31390.
 2007 09  821319.
 2007 10  701397·
 2007 11  371251.
 2007 12  161267.
 2008 01 611218·
 2008 02 201307·
 2008 03 391392.
 2008 04 861359·
 2008 05 31425·
 2008 06 841422·
 2008 07 771445.
 2008 08 71418·
 2008 09 331407·
 2008 10 181348·
 2008 11 371235.
 2008 12 991319.
 2009 01  11220.
 2009 02  41149·
 2009 03  331139.
 2009 04  61172.
 2009 05  841176.
 2009 06  481303.
 2009 07  21310.
 2009 08  961200.
 2009 09  811187·
 2009 10  831059.
 2009 11  81097.
 2009 12  641136·
 2010 01 171183·
 2010 02 651140.
 2010 03 381115·
 2010 04 301169·
 2010 05 441187.
 2010 06 751239.
 2010 07 61326.
 2010 08 371291·
 2010 09 371269·
 2010 10 211213·
 2010 11 481297.
 2010 12 541300.
 2011 01  951208·
 2011 02  331165.
 2011 03  291186.
 2011 04  751229.
 2011 05  451127.
 2011 06  691297.
 2011 07  351320.
 2011 08  211291·
 2011 09  371311·
 2011 10  91312.
 2011 11  811225·
 2011 12  341309.
 2012 01 451284.
 2012 02 621261.
 2012 03 31237.
 2012 04 841281.
 2012 05 711331.
 2012 06 581280.
 2012 07 641319·
 2012 08 651339.
 2012 09 401331·
 2012 10 541366·
 2012 11 531357.
 2012 12 961279.
 2013 01  31307·
 2013 02  321248·
 2013 03  831375·
 2013 04  221295·
 2013 05  341323.
 2013 06  981239.
 2013 07  901312.
 2013 08  111345.
 2013 09  341392·
 2013 10  841358·
 2013 11  391397·
 2013 12  581346·
 2014 01 281292·
 2014 02 461245.
 2014 03 171276·
 2014 04 821246.
 2014 05 681232·
 2014 06 671274.
 2014 07 371296.
 2014 08 261341.
 2014 09 271375.
 2014 10 531375·
 2014 11 361318.
 2014 12 611412·
 2015 01  81410·
 2015 02  351416·
 2015 03  791389.
 2015 04  801372.
 2015 05  341294.
 2015 06  701327.
 2015 07  521405.
 2015 08  21312.
 2015 09  571352.
 2015 10  401347.
 2015 11  681231·
 2015 12  721268·
 2016 01 511299·
 2016 02 521346.
 2016 03 661410.
 2016 04 581458·
 2016 05 181358.
 2016 06 371245.
 2016 07 81166.
 2016 08 551140·
 2016 09 821199.
 2016 10 511221.
 2016 11 821286·
 2016 12 821279.
 2017 01  941305·
 2017 02  771432.
 2017 03  11401·
 2017 04  831472·


 2017 05  301408·
 2017 06  201353·
 2017 07  31300.
 2017 08  271278.
 2017 09  891323.
 2017 10  141322·
 2017 11  511435·
 2017 12  91315·
 2018 01 981384.
 2018 02 131463.
 2018 03 331467.
 2018 04 471386·
 2018 05 61395.
 2018 06 11394·
 2018 07 621268.
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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 Level: Production Occupations, Mexican: 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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