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 Series Title: Employment Level: Nonagriculture, Wage and Salary Workers, 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 128900·
 2000 02 688986.
 2000 03 658998.
 2000 04 879057.
 2000 05 428996·
 2000 06 399169.
 2000 07 929085.
 2000 08 429177.
 2000 09 139435·
 2000 10 849407·
 2000 11 959457·
 2000 12 719627·
 2001 01  759478·
 2001 02  839624·
 2001 03  869489·
 2001 04  189453·
 2001 05  59241.
 2001 06  449226·
 2001 07  49423·
 2001 08  519473·
 2001 09  29615·
 2001 10  999913.
 2001 11  129896·
 2001 12  6610010.
 2002 01 929653·
 2002 02 39716.
 2002 03 979634·
 2002 04 819577.
 2002 05 269772.
 2002 06 409658.
 2002 07 729622.
 2002 08 409724.
 2002 09 789687.
 2002 10 149731.
 2002 11 769982.
 2002 12 139809·
 2003 01  4910156·
 2003 02  5910289.
 2003 03  7110089·
 2003 04  9410220·
 2003 05  6410115·
 2003 06  3010157.
 2003 07  4510109·
 2003 08  19989.
 2003 09  759876.
 2003 10  99975·
 2003 11  1110177·
 2003 12  7910296·
 2004 01 5610002·
 2004 02 410140·
 2004 03 710208·
 2004 04 9710421.
 2004 05 710557·
 2004 06 4410456.
 2004 07 9510444.
 2004 08 5010278·
 2004 09 5410460.
 2004 10 8810604.
 2004 11 6410552.
 2004 12 5510421.
 2005 01  4810181.
 2005 02  1710294.
 2005 03  2710587·
 2005 04  5910912.
 2005 05  6411224·
 2005 06  3711070.
 2005 07  2011077·
 2005 08  2910979.
 2005 09  210899·
 2005 10  8011062.
 2005 11  910984.
 2005 12  5910984.
 2006 01 8710963·
 2006 02 311070·
 2006 03 7911321.
 2006 04 7011374·
 2006 05 7011311·
 2006 06 8811290.
 2006 07 4411381.
 2006 08 511294·
 2006 09 2711408.
 2006 10 4011657.
 2006 11 4211609·
 2006 12 3311679.
 2007 01  5811323.
 2007 02  9211507·
 2007 03  3711636.
 2007 04  4811689.
 2007 05  8711828.
 2007 06  011647·
 2007 07  1411854.
 2007 08  6912003.
 2007 09  6711868·
 2007 10  4611980.
 2007 11  8911660·
 2007 12  4211820·
 2008 01 7111353.
 2008 02 3711427.
 2008 03 9811509.
 2008 04 3411722·
 2008 05 012010·
 2008 06 411771·
 2008 07 411941·
 2008 08 4011914.
 2008 09 8011901·
 2008 10 411801.
 2008 11 9611705·
 2008 12 7911677.
 2009 01  6211316·
 2009 02  1811283·
 2009 03  8511417.
 2009 04  9511471.
 2009 05  1911316·
 2009 06  5311371·
 2009 07  1111311·
 2009 08  5711018·
 2009 09  5411086·
 2009 10  4111094·
 2009 11  3611366.
 2009 12  6011388.
 2010 01 9111289·
 2010 02 3911330·
 2010 03 4811397·
 2010 04 2311308·
 2010 05 8111358·
 2010 06 2711465·
 2010 07 5911321·
 2010 08 8911401.
 2010 09 9811565.
 2010 10 1411283.
 2010 11 811577.
 2010 12 2811506.
 2011 01  4411159.
 2011 02  2911175.
 2011 03  5811284·
 2011 04  3411415·
 2011 05  4411233.
 2011 06  3111347·
 2011 07  9611483·
 2011 08  2711547·
 2011 09  4911663·
 2011 10  011760.
 2011 11  3511818.
 2011 12  4911852·
 2012 01 3211930·
 2012 02 4411970.
 2012 03 1412254·
 2012 04 7112306·
 2012 05 9612244.
 2012 06 9312198·
 2012 07 9412177.
 2012 08 8712209·
 2012 09 6512512.
 2012 10 512458.
 2012 11 6512302.
 2012 12 1612442.
 2013 01  9012375·
 2013 02  6112544.
 2013 03  3812536·
 2013 04  112792.
 2013 05  4712926·
 2013 06  6712693.
 2013 07  5212861.
 2013 08  1212579.
 2013 09  3412698.
 2013 10  5712619·
 2013 11  7012929.
 2013 12  4412958·
 2014 01 7912889.
 2014 02 8513041·
 2014 03 7913077·
 2014 04 1413215·
 2014 05 3113257.
 2014 06 3413290.
 2014 07 9313237·
 2014 08 6813357.
 2014 09 6613184.
 2014 10 1113321·
 2014 11 4913567.
 2014 12 7513705·
 2015 01  8413876·
 2015 02  4613909.
 2015 03  1013796·
 2015 04  2913835.
 2015 05  1113748·
 2015 06  9714012·
 2015 07  6414091·
 2015 08  4813881·
 2015 09  9613769·
 2015 10  4613793·
 2015 11  2513654·
 2015 12  7713729·
 2016 01 1613753.
 2016 02 9813805.
 2016 03 2914006.
 2016 04 8613973·
 2016 05 7014154·
 2016 06 8614140.
 2016 07 4014186·
 2016 08 6713940·
 2016 09 8514026·
 2016 10 6614109·
 2016 11 4614108.
 2016 12 4114072.
 2017 01  1013938.
 2017 02  2014030.
 2017 03  5914295·
 2017 04  5214313.
 2017 05  2014443·
 2017 06  5514600·
 2017 07  1714902·
 2017 08  6814738·
 2017 09  1814451·
 2017 10  214270.
 2017 11  8414486·


 2017 12  8414612·
 2018 01 2614670.
 2018 02 1714858.
 2018 03 4814794·
 2018 04 2014813·
 2018 05 9714787.
 2018 06 8314768·
 2018 07 2014753·
 2018 08 1814788·
 2018 09 514665·
 2018 10 614960.
 2018 11 3915254·
 2018 12 4815401.
 2019 01  5115419·
 2019 02  1715343·
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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: Nonagriculture, Wage and Salary Workers, 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

Sites of Interest: Conerly Consulting: Economics for Business Decisions *

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