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 Series Title: Employment Level: Nonagricultural Industries, Mexican Women: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Yearly Chart  |  Excel file  |  Self-updating Excel file
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 1990 01 572063·
 1990 02 952118·
 1990 03 372162.
 1990 04 652230·
 1990 05 902251·
 1990 06 192343·
 1990 07 662343.
 1990 08 742249.
 1990 09 642102·
 1990 10 172070.
 1990 11 722076.
 1990 12 562074.
 1991 01  292149.
 1991 02  692152.
 1991 03  672161·
 1991 04  552111.
 1991 05  622085·
 1991 06  832099·
 1991 07  882177.
 1991 08  422112·
 1991 09  621990·
 1991 10  912114·
 1991 11  992146.
 1991 12  102211.
 1992 01 562230.
 1992 02 492209·
 1992 03 872282·
 1992 04 782261.
 1992 05 922234.
 1992 06 382296·
 1992 07 662321.
 1992 08 912268.
 1992 09 472191.
 1992 10 662220·
 1992 11 732264·
 1992 12 162265.
 1993 01  222234.
 1993 02  642198.
 1993 03  712313.
 1993 04  502360.
 1993 05  402322.
 1993 06  882342.
 1993 07  482438.
 1993 08  102378.
 1993 09  542356·
 1993 10  202433·
 1993 11  172348.
 1993 12  422378·
 1994 01 382253.
 1994 02 682331.
 1994 03 162438.
 1994 04 132379·
 1994 05 922478·
 1994 06 622424·
 1994 07 72469.
 1994 08 192483·
 1994 09 432518·
 1994 10 592604·
 1994 11 792588·
 1994 12 782551·
 1995 01  402393·
 1995 02  412416·
 1995 03  452450·
 1995 04  342417.
 1995 05  592422.
 1995 06  142499.
 1995 07  422569.
 1995 08  572577.
 1995 09  02666·
 1995 10  102651.
 1995 11  332631.
 1995 12  412561.
 1996 01 882473.
 1996 02 862472·
 1996 03 62475.
 1996 04 52479·
 1996 05 752505·
 1996 06 242515·
 1996 07 752652.
 1996 08 922639·
 1996 09 352765.
 1996 10 292725·
 1996 11 762838.
 1996 12 732837·
 1997 01  682802·
 1997 02  342832.
 1997 03  732783.
 1997 04  422801·
 1997 05  12885.
 1997 06  962861·
 1997 07  542903.
 1997 08  172968·
 1997 09  832875·
 1997 10  952886.
 1997 11  322850.
 1997 12  422907.
 1998 01 912881·
 1998 02 392996.
 1998 03 443026.
 1998 04 873060·
 1998 05 233108·
 1998 06 593084.
 1998 07 543087.
 1998 08 463064·
 1998 09 63112·
 1998 10 123154·
 1998 11 483023.
 1998 12 383091·
 1999 01  913151·
 1999 02  793222.
 1999 03  413309.
 1999 04  83217·
 1999 05  523243·
 1999 06  683241·
 1999 07  703183.
 1999 08  233277·
 1999 09  903203·
 1999 10  93236·
 1999 11  983338.
 1999 12  793491.
 2000 01 303694.
 2000 02 593756·
 2000 03 133625.
 2000 04 953606·
 2000 05 223642·
 2000 06 13635·
 2000 07 273591.
 2000 08 143591.
 2000 09 433843·
 2000 10 413767·
 2000 11 803872.
 2000 12 73981·
 2001 01  923947·
 2001 02  93962·
 2001 03  323891·
 2001 04  663717.
 2001 05  953675.
 2001 06  643716.
 2001 07  733738.
 2001 08  113830.
 2001 09  33884.
 2001 10  863991.
 2001 11  164057.
 2001 12  874149·
 2002 01 904033.
 2002 02 834068.
 2002 03 974074·
 2002 04 623967·
 2002 05 573875.
 2002 06 853957·
 2002 07 813881·
 2002 08 314010·
 2002 09 294069·
 2002 10 503942·
 2002 11 554100.
 2002 12 134067·
 2003 01  574109.
 2003 02  594140·
 2003 03  314041·
 2003 04  514088.
 2003 05  164030·
 2003 06  194080·
 2003 07  484028·
 2003 08  163939·
 2003 09  73906·
 2003 10  623938·
 2003 11  694081·
 2003 12  04047.
 2004 01 553901·
 2004 02 433990·
 2004 03 824011·
 2004 04 244130·
 2004 05 104153.
 2004 06 454106.
 2004 07 994029.
 2004 08 314094.
 2004 09 484196.
 2004 10 754231·
 2004 11 584189.
 2004 12 914181·
 2005 01  694034·
 2005 02  644113·
 2005 03  224183·
 2005 04  984269.
 2005 05  994446·
 2005 06  684302.
 2005 07  804370.
 2005 08  704340.
 2005 09  884342.
 2005 10  694417·
 2005 11  434412·
 2005 12  524316.
 2006 01 104366.
 2006 02 754413·
 2006 03 504443.
 2006 04 144561.
 2006 05 684594.
 2006 06 164629.
 2006 07 644635.
 2006 08 494527.
 2006 09 864524.
 2006 10 494571.
 2006 11 734559.
 2006 12 764670.
 2007 01  144527·
 2007 02  574617·
 2007 03  894639.
 2007 04  404671.
 2007 05  284737.
 2007 06  444777.
 2007 07  514871.
 2007 08  94925·
 2007 09  284873.
 2007 10  444716·
 2007 11  214598·
 2007 12  784711.
 2008 01 404532·
 2008 02 134623·
 2008 03 884598·
 2008 04 674801·
 2008 05 144977.
 2008 06 324868·
 2008 07 634860.
 2008 08 184781·
 2008 09 254811.
 2008 10 84739·
 2008 11 854684·
 2008 12 24781.
 2009 01  744628·
 2009 02  724681·
 2009 03  184762·
 2009 04  124811·
 2009 05  874717·
 2009 06  834692·
 2009 07  484628.
 2009 08  674464.
 2009 09  134629.
 2009 10  204663·
 2009 11  894807.
 2009 12  134899·
 2010 01 284864·
 2010 02 904798·
 2010 03 784812.
 2010 04 174699.
 2010 05 324718·
 2010 06 264707·
 2010 07 794493·
 2010 08 744633·
 2010 09 514807·
 2010 10 844667.
 2010 11 794830·
 2010 12 34742.
 2011 01  364662·
 2011 02  464557·
 2011 03  914715.
 2011 04  484790·
 2011 05  614639·
 2011 06  174641·
 2011 07  544667·
 2011 08  794730.
 2011 09  264887.
 2011 10  314940.
 2011 11  294890.
 2011 12  894912·
 2012 01 595163·
 2012 02 435235·
 2012 03 65351.
 2012 04 985337.
 2012 05 85397.
 2012 06 355364·
 2012 07 965232.
 2012 08 505271·
 2012 09 495377.
 2012 10 135382·
 2012 11 385360.
 2012 12 145450.
 2013 01  825484·
 2013 02  115503·
 2013 03  945369.
 2013 04  845473·
 2013 05  345594·
 2013 06  835527·
 2013 07  535569·
 2013 08  795505·
 2013 09  535531·
 2013 10  125480.
 2013 11  285573·
 2013 12  435567·
 2014 01 175610.
 2014 02 45696.
 2014 03 555726·
 2014 04 465829.
 2014 05 245841·
 2014 06 915942·
 2014 07 995885·
 2014 08 815888·
 2014 09 15779·
 2014 10 305690·
 2014 11 475825.
 2014 12 695746·
 2015 01  985964.
 2015 02  26038.
 2015 03  126078.
 2015 04  526201.
 2015 05  906274·
 2015 06  136416.
 2015 07  316277.
 2015 08  06136·
 2015 09  785999·
 2015 10  976047·
 2015 11  686129·
 2015 12  86079.
 2016 01 866068.
 2016 02 86068.
 2016 03 116233.
 2016 04 946125.
 2016 05 676385·
 2016 06 306218·
 2016 07 726198·
 2016 08 26081·
 2016 09 946093·
 2016 10 676126.
 2016 11 906301.
 2016 12 26281.
 2017 01  686278·
 2017 02  536270.
 2017 03  276382.
 2017 04  886319.
 2017 05  146334·
 2017 06  446301.
 2017 07  716368.
 2017 08  786410.
 2017 09  846289·
 2017 10  216380.
 2017 11  356541.
 2017 12  186571·


 2018 01 526653.
 2018 02 906677.
 2018 03 576540·
 2018 04 766532·
 2018 05 196658.
 2018 06 856565·
 2018 07 06604.
 2018 08 466562·
 2018 09 106535.
 2018 10 616930·
 2018 11 526936·
 2018 12 487106·
 2019 01  767039.
 2019 02  996940·
 2019 03  257005·
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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: Nonagricultural Industries, Mexican Women: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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