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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 68449.
 2000 02 93437·
 2000 03 55435·
 2000 04 25409·
 2000 05 99433.
 2000 06 75445.
 2000 07 52445·
 2000 08 60430.
 2000 09 9391.
 2000 10 67426.
 2000 11 62377.
 2000 12 5405·
 2001 01  48429·
 2001 02  52430·
 2001 03  98470·
 2001 04  7461·
 2001 05  91459.
 2001 06  37403.
 2001 07  99479·
 2001 08  32508·
 2001 09  40483·
 2001 10  52467·
 2001 11  27467.
 2001 12  76449·
 2002 01 19424.
 2002 02 55461·
 2002 03 70473·
 2002 04 58478.
 2002 05 79469.
 2002 06 27422.
 2002 07 40425·
 2002 08 22490.
 2002 09 95481.
 2002 10 75471.
 2002 11 77417.
 2002 12 37416.
 2003 01  67457.
 2003 02  30461.
 2003 03  42459·
 2003 04  97454.
 2003 05  22522·
 2003 06  50513.
 2003 07  23532.
 2003 08  21449·
 2003 09  8435·
 2003 10  15415.
 2003 11  34445.
 2003 12  54438·
 2004 01 3396.
 2004 02 32425·
 2004 03 13471.
 2004 04 64454.
 2004 05 6506·
 2004 06 34534.
 2004 07 21556.
 2004 08 46599.
 2004 09 42535.
 2004 10 76530.
 2004 11 48440·
 2004 12 19449.
 2005 01  62427.
 2005 02  40411·
 2005 03  5532.
 2005 04  27501·
 2005 05  42520·
 2005 06  34563·
 2005 07  32531·
 2005 08  38501·
 2005 09  81491.
 2005 10  88469.
 2005 11  90507.
 2005 12  49535·
 2006 01 5526·
 2006 02 59571.
 2006 03 68612.
 2006 04 76569.
 2006 05 65595·
 2006 06 29580.
 2006 07 78602.
 2006 08 65588·
 2006 09 36633·
 2006 10 4622.
 2006 11 59686.
 2006 12 85776.
 2007 01  17685.
 2007 02  17691.
 2007 03  73663·
 2007 04  30577·
 2007 05  36611.
 2007 06  24639.
 2007 07  9662.
 2007 08  19669.
 2007 09  42600·
 2007 10  6638·
 2007 11  79632·
 2007 12  95684·
 2008 01 10645·
 2008 02 69635.
 2008 03 20609·
 2008 04 29605.
 2008 05 40628·
 2008 06 47603·
 2008 07 97613.
 2008 08 15608.
 2008 09 59606·
 2008 10 95616.
 2008 11 96652.
 2008 12 71635·
 2009 01  17632·
 2009 02  95644.
 2009 03  31639·
 2009 04  41601·
 2009 05  89601.
 2009 06  54571·
 2009 07  39565·
 2009 08  96619·
 2009 09  75617·
 2009 10  3671·
 2009 11  84701·
 2009 12  28710·
 2010 01 1684.
 2010 02 98739·
 2010 03 53775.
 2010 04 58681·
 2010 05 17638.
 2010 06 23631.
 2010 07 60554.
 2010 08 29558·
 2010 09 98576·
 2010 10 82613.
 2010 11 42608·
 2010 12 10616.
 2011 01  46645.
 2011 02  9607.
 2011 03  61621·
 2011 04  96610·
 2011 05  84568·
 2011 06  58611.
 2011 07  7614·
 2011 08  5642.
 2011 09  65625·
 2011 10  13643.
 2011 11  91650·
 2011 12  82703.
 2012 01 63692.
 2012 02 80672.
 2012 03 52644·
 2012 04 96759·
 2012 05 78772·
 2012 06 90741.
 2012 07 53725.
 2012 08 41769.
 2012 09 36763·
 2012 10 0828·
 2012 11 81807·
 2012 12 37792·
 2013 01  87695.
 2013 02  92775.
 2013 03  49782.
 2013 04  26806.
 2013 05  7806·
 2013 06  72832.
 2013 07  96787·
 2013 08  80737·
 2013 09  97734·
 2013 10  72681·
 2013 11  84760.
 2013 12  91736.
 2014 01 80829·
 2014 02 49763.
 2014 03 1779·
 2014 04 78724.
 2014 05 9741.
 2014 06 83830·
 2014 07 60835·
 2014 08 87894·
 2014 09 57841.
 2014 10 83779·
 2014 11 99778·
 2014 12 86817·
 2015 01  27779·
 2015 02  79844.
 2015 03  80870·
 2015 04  69881·
 2015 05  42943.
 2015 06  291008·
 2015 07  92942.
 2015 08  55970.
 2015 09  541053·
 2015 10  13947·
 2015 11  47889·
 2015 12  89956·
 2016 01 37945·
 2016 02 391005·
 2016 03 841009.
 2016 04 391010.
 2016 05 931026.
 2016 06 37984·
 2016 07 65998·
 2016 08 0961.
 2016 09 46951·
 2016 10 66941·
 2016 11 78900·
 2016 12 91912·
 2017 01  481013·
 2017 02  51034.
 2017 03  371098·
 2017 04  561032·
 2017 05  73995·
 2017 06  63927.
 2017 07  78983·
 2017 08  651047·
 2017 09  21968·
 2017 10  71972·
 2017 11  65947.


 2017 12  101000·
 2018 01 191040.
 2018 02 84981·
 2018 03 86998·
 2018 04 13989.
 2018 05 16993.
 2018 06 861061.
 2018 07 531188.
 2018 08 151155.
 2018 09 881095.
 2018 10 821050·
 2018 11 51057.
 2018 12 881160.
 2019 01  351104.
 2019 02  41015.
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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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