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 Series Title: Employment Level: Mexican, Legal 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 4136·
 2000 02 9243·
 2000 03 7830.
 2000 04 8231.
 2000 05 1344.
 2000 06 8044.
 2000 07 9641.
 2000 08 444.
 2000 09 2639.
 2000 10 4230.
 2000 11 9158.
 2000 12 070·
 2001 01  3047.
 2001 02  5852·
 2001 03  7539·
 2001 04  1435·
 2001 05  243·
 2001 06  3747·
 2001 07  8537·
 2001 08  1545.
 2001 09  4251·
 2001 10  851.
 2001 11  8552.
 2001 12  9751·
 2002 01 7441·
 2002 02 3042·
 2002 03 6236·
 2002 04 7931·
 2002 05 5049.
 2002 06 8451·
 2002 07 3034·
 2002 08 531·
 2002 09 4435·
 2002 10 7537.
 2002 11 2651.
 2002 12 4555·
 2003 01  5751.
 2003 02  3752.
 2003 03  1351·
 2003 04  9338·
 2003 05  1534.
 2003 06  2540·
 2003 07  7942.
 2003 08  6734.
 2003 09  6835.
 2003 10  2238·
 2003 11  3756.
 2003 12  1361·
 2004 01 9157·
 2004 02 3346·
 2004 03 2526.
 2004 04 9826·
 2004 05 8434·
 2004 06 9133·
 2004 07 629·
 2004 08 1840·
 2004 09 7437·
 2004 10 5230.
 2004 11 6748.
 2004 12 9145·
 2005 01  1040.
 2005 02  9853·
 2005 03  2264·
 2005 04  6151.
 2005 05  6862.
 2005 06  3666·
 2005 07  869.
 2005 08  9858.
 2005 09  4865.
 2005 10  9669.
 2005 11  8870.
 2005 12  9660.
 2006 01 7562.
 2006 02 3662.
 2006 03 5059·
 2006 04 7456·
 2006 05 160·
 2006 06 3863.
 2006 07 852.
 2006 08 7654·
 2006 09 047.
 2006 10 738·
 2006 11 9841·
 2006 12 7132.
 2007 01  7235.
 2007 02  7633.
 2007 03  8551·
 2007 04  5361·
 2007 05  4466.
 2007 06  247·
 2007 07  5552.
 2007 08  4256·
 2007 09  6647.
 2007 10  6553·
 2007 11  2146·
 2007 12  8251·
 2008 01 1249·
 2008 02 7347.
 2008 03 2353·
 2008 04 4185·
 2008 05 8482.
 2008 06 5780·
 2008 07 2168·
 2008 08 1465.
 2008 09 639.
 2008 10 7443·
 2008 11 562·
 2008 12 2067.
 2009 01  2954·
 2009 02  648·
 2009 03  8737·
 2009 04  436.
 2009 05  2921·
 2009 06  5821.
 2009 07  514·
 2009 08  3319·
 2009 09  635·
 2009 10  6351.
 2009 11  2277.
 2009 12  377.
 2010 01 8563.
 2010 02 7868.
 2010 03 2642.
 2010 04 3332·
 2010 05 1729.
 2010 06 8432.
 2010 07 2929·
 2010 08 6720·
 2010 09 7743·
 2010 10 8739.
 2010 11 7153.
 2010 12 7355·
 2011 01  6557·
 2011 02  2065·
 2011 03  1229·
 2011 04  4635.
 2011 05  834.
 2011 06  3946·
 2011 07  4253.
 2011 08  649.
 2011 09  5450·
 2011 10  2537.
 2011 11  7455·
 2011 12  9657·
 2012 01 8061·
 2012 02 8666·
 2012 03 4565·
 2012 04 8575·
 2012 05 8667.
 2012 06 5291·
 2012 07 1754.
 2012 08 6862·
 2012 09 9757·
 2012 10 8144·
 2012 11 8035·
 2012 12 6327·
 2013 01  6437.
 2013 02  5552.
 2013 03  4570·
 2013 04  1658.
 2013 05  6365.
 2013 06  7984·
 2013 07  5286.
 2013 08  9488.
 2013 09  9372.
 2013 10  8562.
 2013 11  6277.
 2013 12  9370·
 2014 01 8051.
 2014 02 3163·
 2014 03 6363·
 2014 04 3164.
 2014 05 7491.
 2014 06 9789·
 2014 07 6977.
 2014 08 5281·
 2014 09 5159.
 2014 10 9163·
 2014 11 1780·
 2014 12 2673.
 2015 01  1189.
 2015 02  4380.
 2015 03  7166·
 2015 04  4745·
 2015 05  8065.
 2015 06  1269.
 2015 07  1767.
 2015 08  3368·
 2015 09  751·
 2015 10  7757·
 2015 11  7070·
 2015 12  3074·
 2016 01 6963.
 2016 02 4766·
 2016 03 6677.
 2016 04 548·
 2016 05 6675.
 2016 06 5269·
 2016 07 6966.
 2016 08 5474·
 2016 09 2378·
 2016 10 4962·
 2016 11 6790.
 2016 12 9582·
 2017 01  9062.
 2017 02  2179·
 2017 03  7377·
 2017 04  7388·
 2017 05  43100.
 2017 06  7272·


 2017 07  2385.
 2017 08  5762.
 2017 09  8270.
 2017 10  3648·
 2017 11  8367·
 2017 12  4082·
 2018 01 3390·
 2018 02 69106.
 2018 03 38100.
 2018 04 42104·
 2018 05 46114·
 2018 06 52113·
 2018 07 286.
 2018 08 890·
 2018 09 97104·
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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, Legal 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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