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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 25449.
 2000 02 71437.
 2000 03 69435·
 2000 04 78409·
 2000 05 81433.
 2000 06 62445.
 2000 07 10445.
 2000 08 41430·
 2000 09 53391·
 2000 10 1426.
 2000 11 1377.
 2000 12 52405.
 2001 01  91429.
 2001 02  71430·
 2001 03  56470.
 2001 04  56461·
 2001 05  72459.
 2001 06  77403.
 2001 07  13479.
 2001 08  22508·
 2001 09  96483.
 2001 10  51467·
 2001 11  34467·
 2001 12  44449.
 2002 01 87424.
 2002 02 51461.
 2002 03 8473.
 2002 04 41478.
 2002 05 96469.
 2002 06 57422.
 2002 07 47425.
 2002 08 58490.
 2002 09 0481·
 2002 10 76471.
 2002 11 90417·
 2002 12 63416·
 2003 01  97457.
 2003 02  41461·
 2003 03  98459·
 2003 04  51454·
 2003 05  14522·
 2003 06  7513.
 2003 07  61532.
 2003 08  41449.
 2003 09  1435.
 2003 10  56415.
 2003 11  90445.
 2003 12  77438·
 2004 01 32396·
 2004 02 95425.
 2004 03 25471.
 2004 04 27454·
 2004 05 10506·
 2004 06 56534·
 2004 07 27556.
 2004 08 87599.
 2004 09 59535.
 2004 10 95530.
 2004 11 84440·
 2004 12 75449.
 2005 01  29427.
 2005 02  94411·
 2005 03  11532.
 2005 04  36501.
 2005 05  95520.
 2005 06  59563.
 2005 07  43531.
 2005 08  38501·
 2005 09  59491·
 2005 10  22469.
 2005 11  45507.
 2005 12  76535·
 2006 01 46526.
 2006 02 40571.
 2006 03 4612·
 2006 04 69569.
 2006 05 5595.
 2006 06 94580.
 2006 07 33602.
 2006 08 62588.
 2006 09 13633.
 2006 10 91622.
 2006 11 70686.
 2006 12 22776.
 2007 01  70685·
 2007 02  63691·
 2007 03  78663·
 2007 04  44577·
 2007 05  1611.
 2007 06  66639·
 2007 07  44662·
 2007 08  49669·
 2007 09  56600·
 2007 10  82638.
 2007 11  82632.
 2007 12  78684·
 2008 01 12645·
 2008 02 18635·
 2008 03 30609·
 2008 04 3605·
 2008 05 67628.
 2008 06 5603.
 2008 07 50613·
 2008 08 16608.
 2008 09 49606·
 2008 10 99616.
 2008 11 30652.
 2008 12 38635·
 2009 01  6632·
 2009 02  84644.
 2009 03  84639·
 2009 04  11601.
 2009 05  15601·
 2009 06  64571.
 2009 07  48565.
 2009 08  6619.
 2009 09  76617.
 2009 10  72671.
 2009 11  87701.
 2009 12  16710·
 2010 01 14684·
 2010 02 64739·
 2010 03 87775·
 2010 04 61681.
 2010 05 80638·
 2010 06 23631.
 2010 07 62554.
 2010 08 85558·
 2010 09 49576·
 2010 10 54613.
 2010 11 50608.
 2010 12 57616·
 2011 01  21645.
 2011 02  90607·
 2011 03  13621·
 2011 04  70610.
 2011 05  22568·
 2011 06  86611·
 2011 07  40614.
 2011 08  45642.
 2011 09  2625.
 2011 10  25643.
 2011 11  42650·
 2011 12  25703.
 2012 01 37692·
 2012 02 14672.
 2012 03 60644.
 2012 04 80759·
 2012 05 27772·
 2012 06 83741·
 2012 07 54725.
 2012 08 3769·
 2012 09 98763.
 2012 10 90828·
 2012 11 13807·
 2012 12 14792·
 2013 01  99695·
 2013 02  15775.
 2013 03  50782.
 2013 04  56806.
 2013 05  6806.
 2013 06  67832.
 2013 07  3787.
 2013 08  0737·
 2013 09  20734·
 2013 10  76681.
 2013 11  34760·
 2013 12  39736.
 2014 01 66829·
 2014 02 0763·
 2014 03 32779.
 2014 04 92724·
 2014 05 94741·
 2014 06 19830.
 2014 07 10835.
 2014 08 4894·
 2014 09 80841.
 2014 10 40779.
 2014 11 4778·
 2014 12 43817·
 2015 01  24779·
 2015 02  96844.
 2015 03  79870·
 2015 04  3881·
 2015 05  52943·
 2015 06  421008·
 2015 07  22942.
 2015 08  5970·
 2015 09  141053.
 2015 10  60947.
 2015 11  46889.
 2015 12  92956.
 2016 01 85945.
 2016 02 571005·
 2016 03 891009·
 2016 04 331010·
 2016 05 651026.
 2016 06 65984.
 2016 07 14998·
 2016 08 22961·
 2016 09 81951.
 2016 10 40941.
 2016 11 8900·
 2016 12 78912·
 2017 01  821013·
 2017 02  641034·
 2017 03  851098.
 2017 04  461032·
 2017 05  44995·
 2017 06  44927·


 2017 07  82983.
 2017 08  951047.
 2017 09  67968·
 2017 10  10972.
 2017 11  63947·
 2017 12  191000.
 2018 01 771040·
 2018 02 21981·
 2018 03 15998.
 2018 04 36989.
 2018 05 24993.
 2018 06 561061·
 2018 07 511188.
 2018 08 921155·
 2018 09 841095.
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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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