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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 807832.
 2000 02 547902.
 2000 03 127954·
 2000 04 78122·
 2000 05 168081·
 2000 06 188233.
 2000 07 938170.
 2000 08 538250.
 2000 09 888453·
 2000 10 498489.
 2000 11 448505.
 2000 12 668642.
 2001 01  468397.
 2001 02  308579·
 2001 03  778443·
 2001 04  908447·
 2001 05  648330·
 2001 06  658251.
 2001 07  308442.
 2001 08  958384.
 2001 09  448539·
 2001 10  888850.
 2001 11  678900·
 2001 12  758935·
 2002 01 108586.
 2002 02 558677·
 2002 03 758513.
 2002 04 498520·
 2002 05 138757·
 2002 06 478634·
 2002 07 688643·
 2002 08 608685.
 2002 09 298633·
 2002 10 718689·
 2002 11 828920·
 2002 12 808771.
 2003 01  579073·
 2003 02  599307.
 2003 03  819148.
 2003 04  09312·
 2003 05  249138·
 2003 06  679147.
 2003 07  539141.
 2003 08  419050·
 2003 09  798913.
 2003 10  779008·
 2003 11  109167·
 2003 12  479246·
 2004 01 999033.
 2004 02 969138.
 2004 03 929177·
 2004 04 879440.
 2004 05 829535.
 2004 06 559386.
 2004 07 599397·
 2004 08 549173·
 2004 09 569301·
 2004 10 119522.
 2004 11 19479·
 2004 12 699362.
 2005 01  699154·
 2005 02  459284·
 2005 03  309443.
 2005 04  759705.
 2005 05  9910031.
 2005 06  659953.
 2005 07  859970·
 2005 08  419872·
 2005 09  449807.
 2005 10  19884.
 2005 11  279812·
 2005 12  629883.
 2006 01 309840·
 2006 02 119974.
 2006 03 4510156·
 2006 04 5710182.
 2006 05 810129.
 2006 06 7610173.
 2006 07 5210255·
 2006 08 6910221.
 2006 09 5410287·
 2006 10 310457.
 2006 11 8610343.
 2006 12 6810426.
 2007 01  6710144·
 2007 02  2310277·
 2007 03  910495.
 2007 04  4910519.
 2007 05  7210537.
 2007 06  9410469.
 2007 07  1010642·
 2007 08  2910758.
 2007 09  2110660·
 2007 10  9610743·
 2007 11  110445·
 2007 12  5410572·
 2008 01 8910175·
 2008 02 3610288·
 2008 03 2010341.
 2008 04 9210548·
 2008 05 7610692·
 2008 06 4610561·
 2008 07 3110738·
 2008 08 3910649·
 2008 09 710718.
 2008 10 8310613.
 2008 11 2110485·
 2008 12 1110423.
 2009 01  3310135·
 2009 02  289883·
 2009 03  210025.
 2009 04  5510111·
 2009 05  309927.
 2009 06  8810155.
 2009 07  1310088·
 2009 08  399870.
 2009 09  979936·
 2009 10  949894·
 2009 11  1710079.
 2009 12  5710023.
 2010 01 609877.
 2010 02 49927.
 2010 03 210006·
 2010 04 299964·
 2010 05 6910027.
 2010 06 9810047·
 2010 07 8010056.
 2010 08 9710108.
 2010 09 010232·
 2010 10 8410005.
 2010 11 9010316·
 2010 12 3310272.
 2011 01  549935.
 2011 02  939911·
 2011 03  9310000.
 2011 04  2910076·
 2011 05  559962.
 2011 06  8110050·
 2011 07  7910251·
 2011 08  610349.
 2011 09  5410422.
 2011 10  3110543.
 2011 11  6010638.
 2011 12  610585·
 2012 01 2610673·
 2012 02 4910707·
 2012 03 7410953·
 2012 04 9911025.
 2012 05 7210911·
 2012 06 6710848.
 2012 07 8410899·
 2012 08 8010897.
 2012 09 1811164.
 2012 10 4011142.
 2012 11 7711037.
 2012 12 6711073·
 2013 01  1211022·
 2013 02  5211108.
 2013 03  6711074·
 2013 04  511396·
 2013 05  3211448·
 2013 06  811381.
 2013 07  9211465.
 2013 08  6311164.
 2013 09  7711274.
 2013 10  4111277·
 2013 11  1411670.
 2013 12  3511643.
 2014 01 7311494·
 2014 02 611657·
 2014 03 2111648·
 2014 04 3911715.
 2014 05 7011853·
 2014 06 8611991·
 2014 07 2711874.
 2014 08 2112014·
 2014 09 4311844.
 2014 10 8711993·
 2014 11 6812251·
 2014 12 4912359.
 2015 01  9412533·
 2015 02  4112513·
 2015 03  812378·
 2015 04  1812438.
 2015 05  4612290·
 2015 06  412408.
 2015 07  3612575.
 2015 08  4612419.
 2015 09  5112343.
 2015 10  5812442.
 2015 11  6312397·
 2015 12  7812461·
 2016 01 8512491·
 2016 02 1012480·
 2016 03 2712617.
 2016 04 8312583·
 2016 05 4612621.
 2016 06 9212639.
 2016 07 9312811·
 2016 08 5412525·
 2016 09 6212476.
 2016 10 5912627.
 2016 11 4612590·
 2016 12 1212493·
 2017 01  8212416.
 2017 02  9312561·
 2017 03  112748.
 2017 04  112762·


 2017 05  8112950·
 2017 06  313134.
 2017 07  9513456.
 2017 08  8813269.
 2017 09  6112967.
 2017 10  1712710·
 2017 11  9112926.
 2017 12  7012949·
 2018 01 4613076.
 2018 02 9513350.
 2018 03 7713314.
 2018 04 6413226.
 2018 05 8613125.
 2018 06 1713231·
 2018 07 6613258.
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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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