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 Series Title: Employment Level: Mexican, Management Occupations: 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 4449.
 2000 02 27437.
 2000 03 80435.
 2000 04 40409·
 2000 05 10433·
 2000 06 92445.
 2000 07 93445·
 2000 08 49430·
 2000 09 76391·
 2000 10 48426.
 2000 11 0377·
 2000 12 49405.
 2001 01  52429.
 2001 02  79430.
 2001 03  15470·
 2001 04  86461·
 2001 05  15459.
 2001 06  90403·
 2001 07  75479·
 2001 08  29508·
 2001 09  63483.
 2001 10  13467·
 2001 11  43467.
 2001 12  72449·
 2002 01 24424·
 2002 02 5461·
 2002 03 8473·
 2002 04 34478.
 2002 05 46469.
 2002 06 48422.
 2002 07 82425.
 2002 08 59490·
 2002 09 6481·
 2002 10 47471.
 2002 11 3417.
 2002 12 16416·
 2003 01  4457.
 2003 02  36461.
 2003 03  34459.
 2003 04  99454·
 2003 05  64522·
 2003 06  69513·
 2003 07  62532·
 2003 08  28449·
 2003 09  39435·
 2003 10  30415.
 2003 11  1445·
 2003 12  47438.
 2004 01 2396·
 2004 02 24425·
 2004 03 89471.
 2004 04 24454.
 2004 05 55506·
 2004 06 83534·
 2004 07 88556·
 2004 08 55599·
 2004 09 23535·
 2004 10 65530.
 2004 11 87440.
 2004 12 57449.
 2005 01  56427.
 2005 02  49411·
 2005 03  98532·
 2005 04  76501.
 2005 05  29520·
 2005 06  44563·
 2005 07  59531·
 2005 08  81501.
 2005 09  43491.
 2005 10  81469·
 2005 11  33507·
 2005 12  64535.
 2006 01 24526·
 2006 02 17571.
 2006 03 8612·
 2006 04 47569·
 2006 05 21595.
 2006 06 32580.
 2006 07 96602.
 2006 08 72588·
 2006 09 11633·
 2006 10 34622.
 2006 11 37686.
 2006 12 9776·
 2007 01  93685.
 2007 02  55691·
 2007 03  92663.
 2007 04  52577·
 2007 05  92611.
 2007 06  51639.
 2007 07  49662·
 2007 08  21669.
 2007 09  61600.
 2007 10  3638·
 2007 11  22632.
 2007 12  58684·
 2008 01 72645.
 2008 02 19635.
 2008 03 48609.
 2008 04 35605·
 2008 05 28628·
 2008 06 29603·
 2008 07 90613·
 2008 08 44608.
 2008 09 54606.
 2008 10 91616.
 2008 11 36652·
 2008 12 4635·
 2009 01  99632·
 2009 02  87644.
 2009 03  99639·
 2009 04  61601·
 2009 05  40601.
 2009 06  22571.
 2009 07  17565·
 2009 08  83619.
 2009 09  76617.
 2009 10  29671·
 2009 11  53701.
 2009 12  64710·
 2010 01 33684.
 2010 02 64739·
 2010 03 94775·
 2010 04 23681.
 2010 05 61638.
 2010 06 8631.
 2010 07 54554·
 2010 08 5558·
 2010 09 37576.
 2010 10 70613·
 2010 11 70608·
 2010 12 78616·
 2011 01  59645.
 2011 02  79607·
 2011 03  5621.
 2011 04  38610.
 2011 05  55568·
 2011 06  93611.
 2011 07  48614.
 2011 08  2642·
 2011 09  73625·
 2011 10  93643.
 2011 11  11650·
 2011 12  15703·
 2012 01 89692·
 2012 02 86672.
 2012 03 31644.
 2012 04 46759.
 2012 05 5772·
 2012 06 4741.
 2012 07 73725.
 2012 08 90769·
 2012 09 44763·
 2012 10 4828·
 2012 11 23807.
 2012 12 65792·
 2013 01  58695·
 2013 02  66775·
 2013 03  94782.
 2013 04  16806·
 2013 05  22806.
 2013 06  97832.
 2013 07  26787·
 2013 08  12737.
 2013 09  36734·
 2013 10  30681.
 2013 11  79760.
 2013 12  46736.
 2014 01 26829.
 2014 02 21763·
 2014 03 43779·
 2014 04 39724·
 2014 05 42741.
 2014 06 51830·
 2014 07 30835.
 2014 08 33894.
 2014 09 60841.
 2014 10 28779.
 2014 11 78778.
 2014 12 99817·
 2015 01  79779·
 2015 02  82844.
 2015 03  50870.
 2015 04  31881.
 2015 05  26943·
 2015 06  711008.
 2015 07  34942·
 2015 08  47970.
 2015 09  501053.
 2015 10  75947·
 2015 11  43889·
 2015 12  92956·
 2016 01 28945.
 2016 02 21005·
 2016 03 141009.
 2016 04 341010·
 2016 05 581026·
 2016 06 84984.
 2016 07 11998.
 2016 08 69961.
 2016 09 68951·
 2016 10 77941.
 2016 11 21900·
 2016 12 15912·
 2017 01  71013·
 2017 02  621034.
 2017 03  581098.
 2017 04  161032·
 2017 05  51995·
 2017 06  46927.
 2017 07  59983·
 2017 08  421047·


 2017 09  99968.
 2017 10  62972·
 2017 11  86947·
 2017 12  861000·
 2018 01 781040·
 2018 02 64981·
 2018 03 29998.
 2018 04 68989·
 2018 05 38993·
 2018 06 361061.
 2018 07 01188.
 2018 08 321155.
 2018 09 541095.
 2018 10 841050.
 2018 11 361057.
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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: Mexican, Management Occupations: 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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