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 Series Title: Employment Level: Management, Professional, and Related 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 501464.
 2000 02 181464.
 2000 03 621382.
 2000 04 101343.
 2000 05 141380.
 2000 06 281419·
 2000 07 81385·
 2000 08 391403.
 2000 09 891415·
 2000 10 811367.
 2000 11 991382·
 2000 12 111453.
 2001 01  241410·
 2001 02  581432·
 2001 03  471525·
 2001 04  701494·
 2001 05  951462.
 2001 06  651353·
 2001 07  911473.
 2001 08  841560.
 2001 09  31534.
 2001 10  341567·
 2001 11  931452.
 2001 12  471503·
 2002 01 711476·
 2002 02 231441.
 2002 03 411521·
 2002 04 801513·
 2002 05 521517.
 2002 06 111539.
 2002 07 491462·
 2002 08 261547.
 2002 09 211544·
 2002 10 71572·
 2002 11 531495·
 2002 12 541504·
 2003 01  771656·
 2003 02  411568.
 2003 03  181552.
 2003 04  591504·
 2003 05  471575.
 2003 06  711613.
 2003 07  301528.
 2003 08  591463.
 2003 09  801525.
 2003 10  771538·
 2003 11  31648·
 2003 12  991641·
 2004 01 521481.
 2004 02 671490.
 2004 03 741510.
 2004 04 471547.
 2004 05 631693.
 2004 06 731669.
 2004 07 71673.
 2004 08 991704.
 2004 09 391726·
 2004 10 501681·
 2004 11 891656·
 2004 12 731612.
 2005 01  311537·
 2005 02  811551.
 2005 03  331727·
 2005 04  131749.
 2005 05  131796.
 2005 06  721757·
 2005 07  781669·
 2005 08  881612·
 2005 09  851648·
 2005 10  551709·
 2005 11  861730.
 2005 12  931756.
 2006 01 751802·
 2006 02 871844.
 2006 03 441881.
 2006 04 461781·
 2006 05 311810.
 2006 06 481686.
 2006 07 661729·
 2006 08 921737.
 2006 09 291834·
 2006 10 471856.
 2006 11 901960.
 2006 12 12035.
 2007 01  691961.
 2007 02  131969·
 2007 03  791907.
 2007 04  651903·
 2007 05  781917·
 2007 06  51906·
 2007 07  201893·
 2007 08  41997·
 2007 09  41966.
 2007 10  41974.
 2007 11  261939·
 2007 12  632071.
 2008 01 251956.
 2008 02 151917·
 2008 03 361895·
 2008 04 111929.
 2008 05 391991·
 2008 06 721905·
 2008 07 121903·
 2008 08 411954.
 2008 09 732007·
 2008 10 301998.
 2008 11 412073.
 2008 12 732069·
 2009 01  772028.
 2009 02  722091·
 2009 03  382030.
 2009 04  512060·
 2009 05  262068·
 2009 06  31967.
 2009 07  401943·
 2009 08  431970.
 2009 09  212008·
 2009 10  562085.
 2009 11  92208·
 2009 12  452191.
 2010 01 872236·
 2010 02 872251.
 2010 03 342219.
 2010 04 762072.
 2010 05 742047.
 2010 06 782007·
 2010 07 271799·
 2010 08 791845·
 2010 09 581899.
 2010 10 351984·
 2010 11 271998·
 2010 12 232033.
 2011 01  392060·
 2011 02  902121·
 2011 03  962116·
 2011 04  42077.
 2011 05  431971.
 2011 06  02044.
 2011 07  222015·
 2011 08  392072·
 2011 09  202077·
 2011 10  472038.
 2011 11  181999.
 2011 12  732111.
 2012 01 452212.
 2012 02 362307.
 2012 03 222380.
 2012 04 762490.
 2012 05 192411.
 2012 06 02348·
 2012 07 972132·
 2012 08 402303.
 2012 09 672379·
 2012 10 962467.
 2012 11 312429.
 2012 12 872475.
 2013 01  392361·
 2013 02  42436.
 2013 03  362477·
 2013 04  592491.
 2013 05  122533.
 2013 06  322485·
 2013 07  512429.
 2013 08  252362.
 2013 09  852465·
 2013 10  112294·
 2013 11  382407.
 2013 12  812346·
 2014 01 832464.
 2014 02 982508.
 2014 03 862571·
 2014 04 442560·
 2014 05 582543.
 2014 06 742698.
 2014 07 62705·
 2014 08 602720.
 2014 09 842645·
 2014 10 462603.
 2014 11 382561.
 2014 12 972597.
 2015 01  622679·
 2015 02  472831.
 2015 03  442891.
 2015 04  502798·
 2015 05  172942.
 2015 06  313025.
 2015 07  112804.
 2015 08  372873.
 2015 09  02890·
 2015 10  822892·
 2015 11  542938·
 2015 12  32898·
 2016 01 862858.
 2016 02 52888.
 2016 03 82917·
 2016 04 172932.
 2016 05 762974.
 2016 06 332897.
 2016 07 392923.
 2016 08 722873·
 2016 09 942995.
 2016 10 222978·
 2016 11 332891·
 2016 12 893018.
 2017 01  923021.
 2017 02  533112.
 2017 03  33172.
 2017 04  123094.
 2017 05  442959·
 2017 06  342962·


 2017 07  873050.
 2017 08  83029.
 2017 09  513175.
 2017 10  953103.
 2017 11  483216.
 2017 12  743277.
 2018 01 383322.
 2018 02 943271.
 2018 03 753182·
 2018 04 273265.
 2018 05 573112·
 2018 06 123100·
 2018 07 793242.
 2018 08 113132·
 2018 09 813123·
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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: Management, Professional, and Related 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

New data set: Quarterly Financial Reporting: Manufacturing, Mining, Trade, and Selected Service Industries

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