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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 141015.
 2000 02 171019.
 2000 03 831067.
 2000 04 91046·
 2000 05 151132·
 2000 06 251220.
 2000 07 631176.
 2000 08 831222·
 2000 09 211208.
 2000 10 701183.
 2000 11 811110·
 2000 12 931138·
 2001 01  811126.
 2001 02  321189·
 2001 03  511168·
 2001 04  841210·
 2001 05  701260·
 2001 06  181254.
 2001 07  101203·
 2001 08  241186·
 2001 09  891217.
 2001 10  601279·
 2001 11  211362.
 2001 12  81414.
 2002 01 641374·
 2002 02 151401·
 2002 03 721238·
 2002 04 541252·
 2002 05 441303·
 2002 06 641299·
 2002 07 761265·
 2002 08 71229.
 2002 09 61301.
 2002 10 141322.
 2002 11 701422·
 2002 12 361287.
 2003 01  491239·
 2003 02  961198.
 2003 03  181246·
 2003 04  361304·
 2003 05  991370·
 2003 06  681489.
 2003 07  81452·
 2003 08  241528.
 2003 09  71544·
 2003 10  101509·
 2003 11  521445·
 2003 12  471509.
 2004 01 471462.
 2004 02 291493·
 2004 03 891493.
 2004 04 711564·
 2004 05 211640·
 2004 06 581711.
 2004 07 811668·
 2004 08 931604.
 2004 09 531590·
 2004 10 521529.
 2004 11 151672.
 2004 12 301625.
 2005 01  931580.
 2005 02  931681·
 2005 03  61659.
 2005 04  271696·
 2005 05  191811·
 2005 06  881823.
 2005 07  911936.
 2005 08  541911.
 2005 09  291863.
 2005 10  691946·
 2005 11  321946.
 2005 12  31804·
 2006 01 491825.
 2006 02 931935·
 2006 03 181938.
 2006 04 952026·
 2006 05 292054·
 2006 06 401984.
 2006 07 622007·
 2006 08 741998.
 2006 09 452119·
 2006 10 172067.
 2006 11 12138.
 2006 12 82195.
 2007 01  982082.
 2007 02  572151·
 2007 03  992219.
 2007 04  922132.
 2007 05  122159.
 2007 06  152096.
 2007 07  422067·
 2007 08  452029.
 2007 09  381963·
 2007 10  742067·
 2007 11  452102.
 2007 12  122082.
 2008 01 521958·
 2008 02 401927.
 2008 03 451862·
 2008 04 601911·
 2008 05 541817·
 2008 06 441921.
 2008 07 41982·
 2008 08 851923.
 2008 09 681921·
 2008 10 441790.
 2008 11 121742·
 2008 12 51741·
 2009 01  471611·
 2009 02  211536.
 2009 03  801604·
 2009 04  661640·
 2009 05  641559·
 2009 06  821625·
 2009 07  471491.
 2009 08  341491.
 2009 09  211522.
 2009 10  581535·
 2009 11  751505·
 2009 12  61416·
 2010 01 421420.
 2010 02 51448.
 2010 03 521499·
 2010 04 01563.
 2010 05 791545.
 2010 06 71671·
 2010 07 921646·
 2010 08 611561.
 2010 09 61500.
 2010 10 681379.
 2010 11 321466·
 2010 12 561435·
 2011 01  241359.
 2011 02  211504.
 2011 03  351446.
 2011 04  811504·
 2011 05  591485·
 2011 06  231505.
 2011 07  891520.
 2011 08  551590·
 2011 09  601569.
 2011 10  551569·
 2011 11  61699·
 2011 12  221618.
 2012 01 41481·
 2012 02 241420·
 2012 03 251409.
 2012 04 501363.
 2012 05 901408.
 2012 06 611401.
 2012 07 91475.
 2012 08 351526.
 2012 09 431529·
 2012 10 231500·
 2012 11 461469·
 2012 12 951478.
 2013 01  151475·
 2013 02  911506.
 2013 03  471494·
 2013 04  741503.
 2013 05  811548.
 2013 06  741728.
 2013 07  521719·
 2013 08  421625·
 2013 09  411615.
 2013 10  01517·
 2013 11  231607·
 2013 12  921598·
 2014 01 201507.
 2014 02 291714.
 2014 03 481678.
 2014 04 441778·
 2014 05 691842·
 2014 06 411757·
 2014 07 401780.
 2014 08 421742.
 2014 09 641726·
 2014 10 431757·
 2014 11 371833·
 2014 12 561751.
 2015 01  41689.
 2015 02  661746.
 2015 03  21687·
 2015 04  781861.
 2015 05  151787·
 2015 06  671660.
 2015 07  221786.
 2015 08  291702.
 2015 09  471737·
 2015 10  281744·
 2015 11  111809·
 2015 12  521787.
 2016 01 771729.
 2016 02 561814.
 2016 03 61730·
 2016 04 171760·
 2016 05 31790.
 2016 06 811868.
 2016 07 701891.
 2016 08 171887.
 2016 09 522001.
 2016 10 621857.
 2016 11 911913·
 2016 12 731967·
 2017 01  741860.
 2017 02  791770.
 2017 03  831861.
 2017 04  272022.
 2017 05  452170·
 2017 06  382134·
 2017 07  822064.
 2017 08  502054·
 2017 09  642004·


 2017 10  732049.
 2017 11  532200·
 2017 12  352134.
 2018 01 572228·
 2018 02 382049.
 2018 03 822019.
 2018 04 22088.
 2018 05 752035.
 2018 06 172022.
 2018 07 821956·
 2018 08 941947·
 2018 09 932045.
 2018 10 152054·
 2018 11 922255·
 2018 12 812151·
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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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