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 Series Title: Employment Level: Construction and Extraction Occupations, 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 951015.
 2000 02 941019·
 2000 03 441067.
 2000 04 411046·
 2000 05 61132·
 2000 06 621220.
 2000 07 331176·
 2000 08 741222.
 2000 09 211208·
 2000 10 661183·
 2000 11 611110.
 2000 12 441138·
 2001 01  901126·
 2001 02  871189·
 2001 03  401168.
 2001 04  941210.
 2001 05  881260.
 2001 06  331254·
 2001 07  81203.
 2001 08  931186·
 2001 09  171217.
 2001 10  351279·
 2001 11  291362·
 2001 12  361414·
 2002 01 11374·
 2002 02 491401.
 2002 03 891238·
 2002 04 421252·
 2002 05 911303.
 2002 06 571299·
 2002 07 21265.
 2002 08 551229.
 2002 09 621301·
 2002 10 661322·
 2002 11 61422.
 2002 12 431287.
 2003 01  151239.
 2003 02  81198·
 2003 03  641246.
 2003 04  21304·
 2003 05  741370.
 2003 06  391489·
 2003 07  631452·
 2003 08  501528·
 2003 09  911544.
 2003 10  401509·
 2003 11  161445.
 2003 12  321509.
 2004 01 411462.
 2004 02 191493.
 2004 03 621493·
 2004 04 161564·
 2004 05 241640.
 2004 06 71711.
 2004 07 631668.
 2004 08 971604.
 2004 09 651590.
 2004 10 601529·
 2004 11 81672.
 2004 12 931625·
 2005 01  151580·
 2005 02  611681.
 2005 03  81659.
 2005 04  501696·
 2005 05  501811.
 2005 06  161823.
 2005 07  21936.
 2005 08  361911·
 2005 09  691863·
 2005 10  561946.
 2005 11  531946.
 2005 12  451804·
 2006 01 981825.
 2006 02 391935·
 2006 03 481938·
 2006 04 962026.
 2006 05 882054.
 2006 06 451984·
 2006 07 12007·
 2006 08 341998.
 2006 09 142119.
 2006 10 822067·
 2006 11 502138.
 2006 12 282195.
 2007 01  762082.
 2007 02  812151.
 2007 03  562219.
 2007 04  712132.
 2007 05  02159·
 2007 06  992096·
 2007 07  92067·
 2007 08  842029·
 2007 09  351963·
 2007 10  172067·
 2007 11  222102.
 2007 12  92082·
 2008 01 581958·
 2008 02 421927·
 2008 03 311862·
 2008 04 171911.
 2008 05 691817·
 2008 06 61921.
 2008 07 01982·
 2008 08 11923·
 2008 09 931921·
 2008 10 651790·
 2008 11 171742·
 2008 12 811741.
 2009 01  811611·
 2009 02  21536·
 2009 03  941604.
 2009 04  11640.
 2009 05  81559·
 2009 06  221625.
 2009 07  701491·
 2009 08  291491.
 2009 09  741522.
 2009 10  571535·
 2009 11  81505·
 2009 12  601416.
 2010 01 51420.
 2010 02 641448.
 2010 03 941499.
 2010 04 141563.
 2010 05 511545·
 2010 06 251671·
 2010 07 441646.
 2010 08 331561·
 2010 09 871500.
 2010 10 461379·
 2010 11 931466.
 2010 12 881435·
 2011 01  151359.
 2011 02  581504.
 2011 03  51446·
 2011 04  731504.
 2011 05  591485.
 2011 06  191505·
 2011 07  681520·
 2011 08  61590·
 2011 09  701569.
 2011 10  111569·
 2011 11  951699.
 2011 12  321618·
 2012 01 221481.
 2012 02 391420.
 2012 03 241409·
 2012 04 201363.
 2012 05 181408.
 2012 06 351401.
 2012 07 171475·
 2012 08 641526·
 2012 09 811529.
 2012 10 561500.
 2012 11 631469.
 2012 12 831478.
 2013 01  621475.
 2013 02  841506·
 2013 03  741494.
 2013 04  221503·
 2013 05  371548·
 2013 06  261728·
 2013 07  881719.
 2013 08  491625·
 2013 09  71615·
 2013 10  121517·
 2013 11  691607.
 2013 12  581598.
 2014 01 951507.
 2014 02 01714·
 2014 03 31678.
 2014 04 701778.
 2014 05 541842.
 2014 06 711757.
 2014 07 41780·
 2014 08 271742.
 2014 09 581726.
 2014 10 321757.
 2014 11 111833.
 2014 12 01751.
 2015 01  71689·
 2015 02  151746.
 2015 03  851687.
 2015 04  821861.
 2015 05  271787.
 2015 06  761660.
 2015 07  141786.
 2015 08  921702·
 2015 09  691737.
 2015 10  961744.
 2015 11  121809·
 2015 12  741787.
 2016 01 81729.
 2016 02 831814.
 2016 03 171730.
 2016 04 991760.
 2016 05 441790·
 2016 06 681868·
 2016 07 901891.
 2016 08 591887.
 2016 09 22001·
 2016 10 81857.
 2016 11 211913·
 2016 12 741967.
 2017 01  341860.
 2017 02  841770·
 2017 03  221861.
 2017 04  882022.
 2017 05  132170·
 2017 06  32134·


 2017 07  312064.
 2017 08  702054.
 2017 09  422004.
 2017 10  972049·
 2017 11  102200·
 2017 12  142134.
 2018 01 452228.
 2018 02 222049.
 2018 03 492019.
 2018 04 402088·
 2018 05 722035·
 2018 06 602022·
 2018 07 591956·
 2018 08 921947.
 2018 09 992045·
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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: Construction and Extraction Occupations, 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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