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 Series Title: Employment Level: Mexican, Natural Resources, Construction, and Maintenance 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 751746·
 2000 02 511764.
 2000 03 281810·
 2000 04 341921.
 2000 05 212058·
 2000 06 432144.
 2000 07 552120·
 2000 08 442176·
 2000 09 772067.
 2000 10 771973·
 2000 11 271869.
 2000 12 971863·
 2001 01  931830·
 2001 02  351892.
 2001 03  571863.
 2001 04  372049.
 2001 05  452153.
 2001 06  232084.
 2001 07  821972·
 2001 08  322002·
 2001 09  342049·
 2001 10  742105.
 2001 11  652115·
 2001 12  772144·
 2002 01 842072·
 2002 02 432093·
 2002 03 951879.
 2002 04 912041·
 2002 05 462068.
 2002 06 132140·
 2002 07 832186.
 2002 08 182044·
 2002 09 962165.
 2002 10 902156.
 2002 11 692063·
 2002 12 281966·
 2003 01  331982·
 2003 02  51999·
 2003 03  152053·
 2003 04  142071·
 2003 05  842186.
 2003 06  162285.
 2003 07  82293·
 2003 08  952458.
 2003 09  982585·
 2003 10  42480·
 2003 11  622215·
 2003 12  162305·
 2004 01 522227·
 2004 02 752260.
 2004 03 152278.
 2004 04 462399.
 2004 05 442485·
 2004 06 622510.
 2004 07 292476·
 2004 08 792498.
 2004 09 22451.
 2004 10 212371·
 2004 11 922529·
 2004 12 342401·
 2005 01  742275.
 2005 02  332406.
 2005 03  182427·
 2005 04  552478·
 2005 05  382640·
 2005 06  52686·
 2005 07  442827·
 2005 08  112854·
 2005 09  922724·
 2005 10  702769.
 2005 11  332783.
 2005 12  972529·
 2006 01 622558·
 2006 02 822698·
 2006 03 722638·
 2006 04 322801.
 2006 05 992874·
 2006 06 252832·
 2006 07 762864·
 2006 08 602834·
 2006 09 792957·
 2006 10 52880·
 2006 11 812926·
 2006 12 492954·
 2007 01  12817·
 2007 02  532928.
 2007 03  512998·
 2007 04  952850.
 2007 05  902914·
 2007 06  262891.
 2007 07  732902.
 2007 08  162839.
 2007 09  982814.
 2007 10  52913·
 2007 11  612946.
 2007 12  562935·
 2008 01 02843.
 2008 02 982788·
 2008 03 522720.
 2008 04 842750.
 2008 05 962625.
 2008 06 362715.
 2008 07 92797·
 2008 08 962762.
 2008 09 112821·
 2008 10 762622.
 2008 11 202519·
 2008 12 92522·
 2009 01  962369.
 2009 02  982327·
 2009 03  982411.
 2009 04  682494·
 2009 05  262407.
 2009 06  112475.
 2009 07  802318·
 2009 08  422263.
 2009 09  22327.
 2009 10  452286.
 2009 11  312279·
 2009 12  252201.
 2010 01 492147.
 2010 02 572188.
 2010 03 372275.
 2010 04 372391.
 2010 05 182455·
 2010 06 292630·
 2010 07 122639·
 2010 08 212511.
 2010 09 832475·
 2010 10 682353·
 2010 11 932397·
 2010 12 472332·
 2011 01  452097.
 2011 02  52332.
 2011 03  432207.
 2011 04  82285·
 2011 05  312397.
 2011 06  962418·
 2011 07  502506·
 2011 08  252514·
 2011 09  892482.
 2011 10  242479·
 2011 11  282597.
 2011 12  402522·
 2012 01 952388.
 2012 02 942293.
 2012 03 132186·
 2012 04 242153·
 2012 05 502224.
 2012 06 392290.
 2012 07 692451.
 2012 08 702450.
 2012 09 792537·
 2012 10 162498·
 2012 11 842365·
 2012 12 982392·
 2013 01  332281·
 2013 02  62332·
 2013 03  712311.
 2013 04  512358·
 2013 05  872486.
 2013 06  152594.
 2013 07  672703·
 2013 08  992596·
 2013 09  412570·
 2013 10  752503.
 2013 11  352525.
 2013 12  362419·
 2014 01 212356·
 2014 02 432535·
 2014 03 642459·
 2014 04 802631·
 2014 05 772785·
 2014 06 12730.
 2014 07 662739·
 2014 08 772723.
 2014 09 842717.
 2014 10 542731.
 2014 11 792831·
 2014 12 962662.
 2015 01  432712.
 2015 02  362776.
 2015 03  662748.
 2015 04  302872·
 2015 05  802720·
 2015 06  22693.
 2015 07  152872.
 2015 08  982792.
 2015 09  442909.
 2015 10  342875.
 2015 11  382896·
 2015 12  452831·
 2016 01 112707·
 2016 02 382759·
 2016 03 742712·
 2016 04 402692.
 2016 05 822778·
 2016 06 472924.
 2016 07 862997·
 2016 08 773066·
 2016 09 823138.
 2016 10 172942.
 2016 11 612944.
 2016 12 752907·
 2017 01  602838.
 2017 02  302718·
 2017 03  122953·
 2017 04  793091·
 2017 05  943235.
 2017 06  923231.
 2017 07  783164.
 2017 08  573179·
 2017 09  823209·
 2017 10  343192·
 2017 11  203289·


 2017 12  33130·
 2018 01 513168.
 2018 02 143096·
 2018 03 283039.
 2018 04 383075·
 2018 05 513100·
 2018 06 143045.
 2018 07 143106.
 2018 08 43071.
 2018 09 573225·
 2018 10 393133·
 2018 11 153361.
 2018 12 713227·
 2019 01  693307·
 2019 02  223257.
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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, Natural Resources, Construction, and Maintenance 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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