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 Series Title: Employment Level: Nonagriculture, Private 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 307832.
 2000 02 227902.
 2000 03 27954.
 2000 04 678122.
 2000 05 388081.
 2000 06 378233·
 2000 07 888170.
 2000 08 478250·
 2000 09 498453·
 2000 10 878489.
 2000 11 138505·
 2000 12 648642.
 2001 01  158397·
 2001 02  568579.
 2001 03  898443.
 2001 04  618447.
 2001 05  118330·
 2001 06  488251.
 2001 07  548442·
 2001 08  78384·
 2001 09  368539·
 2001 10  978850·
 2001 11  718900.
 2001 12  978935·
 2002 01 178586·
 2002 02 588677.
 2002 03 298513.
 2002 04 508520.
 2002 05 48757·
 2002 06 138634·
 2002 07 398643·
 2002 08 98685·
 2002 09 728633·
 2002 10 698689.
 2002 11 398920·
 2002 12 458771·
 2003 01  219073.
 2003 02  589307·
 2003 03  949148.
 2003 04  509312.
 2003 05  789138·
 2003 06  359147.
 2003 07  909141.
 2003 08  459050·
 2003 09  928913.
 2003 10  849008·
 2003 11  409167·
 2003 12  749246.
 2004 01 389033.
 2004 02 99138.
 2004 03 839177·
 2004 04 59440.
 2004 05 189535·
 2004 06 449386.
 2004 07 819397·
 2004 08 329173.
 2004 09 569301·
 2004 10 449522.
 2004 11 229479.
 2004 12 769362.
 2005 01  39154.
 2005 02  929284·
 2005 03  199443.
 2005 04  799705.
 2005 05  3510031·
 2005 06  949953.
 2005 07  109970·
 2005 08  129872·
 2005 09  519807·
 2005 10  819884·
 2005 11  589812.
 2005 12  689883·
 2006 01 779840·
 2006 02 109974.
 2006 03 5010156·
 2006 04 6610182.
 2006 05 6410129·
 2006 06 6310173·
 2006 07 010255.
 2006 08 5110221.
 2006 09 8610287.
 2006 10 4710457·
 2006 11 4510343·
 2006 12 9110426.
 2007 01  4510144·
 2007 02  9310277·
 2007 03  4910495.
 2007 04  8210519·
 2007 05  6610537.
 2007 06  5810469·
 2007 07  9910642.
 2007 08  4110758.
 2007 09  9810660·
 2007 10  2310743.
 2007 11  810445.
 2007 12  1410572.
 2008 01 1810175.
 2008 02 9510288.
 2008 03 1410341·
 2008 04 6810548.
 2008 05 2610692·
 2008 06 610561·
 2008 07 8010738.
 2008 08 010649·
 2008 09 4710718·
 2008 10 1210613·
 2008 11 9410485·
 2008 12 2610423·
 2009 01  3210135·
 2009 02  959883·
 2009 03  6810025·
 2009 04  9310111·
 2009 05  559927·
 2009 06  6210155·
 2009 07  4110088.
 2009 08  689870·
 2009 09  189936.
 2009 10  449894.
 2009 11  7510079·
 2009 12  4610023.
 2010 01 469877·
 2010 02 989927·
 2010 03 5910006·
 2010 04 469964.
 2010 05 8910027·
 2010 06 610047.
 2010 07 510056·
 2010 08 1310108·
 2010 09 2210232.
 2010 10 7310005·
 2010 11 5110316.
 2010 12 1510272·
 2011 01  479935.
 2011 02  339911.
 2011 03  6010000.
 2011 04  4610076·
 2011 05  889962.
 2011 06  4110050·
 2011 07  2010251.
 2011 08  2610349·
 2011 09  9510422.
 2011 10  7910543·
 2011 11  4410638.
 2011 12  9910585.
 2012 01 4510673·
 2012 02 5410707.
 2012 03 7010953.
 2012 04 3411025.
 2012 05 3710911·
 2012 06 9710848.
 2012 07 6010899.
 2012 08 2410897·
 2012 09 9711164.
 2012 10 6511142.
 2012 11 211037.
 2012 12 9111073·
 2013 01  7511022·
 2013 02  4011108·
 2013 03  1011074.
 2013 04  7611396.
 2013 05  4711448·
 2013 06  2911381·
 2013 07  2111465·
 2013 08  5011164.
 2013 09  1311274.
 2013 10  6211277.
 2013 11  9911670.
 2013 12  711643.
 2014 01 9911494·
 2014 02 9711657.
 2014 03 3011648·
 2014 04 6511715·
 2014 05 5411853·
 2014 06 1511991·
 2014 07 2811874.
 2014 08 6912014.
 2014 09 5511844.
 2014 10 2311993.
 2014 11 3212251.
 2014 12 8912359.
 2015 01  112533.
 2015 02  5212513.
 2015 03  212378.
 2015 04  1712438·
 2015 05  1912290.
 2015 06  6012408.
 2015 07  2912575.
 2015 08  7412419.
 2015 09  5712343·
 2015 10  2712442·
 2015 11  2412397.
 2015 12  412461·
 2016 01 9312491.
 2016 02 6112480·
 2016 03 2512617·
 2016 04 7512583.
 2016 05 2612621·
 2016 06 9312639.
 2016 07 9612811·
 2016 08 8212525.
 2016 09 8112476.
 2016 10 7912627·
 2016 11 2312590.
 2016 12 4412493·
 2017 01  912416.
 2017 02  212561·
 2017 03  2112748·
 2017 04  412762.
 2017 05  8612950·
 2017 06  6813134·


 2017 07  2713456.
 2017 08  3313269·
 2017 09  1112967.
 2017 10  912710·
 2017 11  312926.
 2017 12  2512949·
 2018 01 1113076·
 2018 02 8113350·
 2018 03 3813314·
 2018 04 9813226.
 2018 05 3513125·
 2018 06 6613231.
 2018 07 4513258·
 2018 08 9613362·
 2018 09 5913206·
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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, Private 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

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