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 Series Title: Employment Level: Construction and Extraction Occupations in Manufacturing Industry: 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 84412.
 2000 02 88458·
 2000 03 83444.
 2000 04 21496.
 2000 05 78530.
 2000 06 35528.
 2000 07 72485.
 2000 08 99454.
 2000 09 8425.
 2000 10 49388·
 2000 11 30356.
 2000 12 44400.
 2001 01  23403·
 2001 02  12408·
 2001 03  71447.
 2001 04  1470.
 2001 05  99473.
 2001 06  31497.
 2001 07  32446.
 2001 08  39421·
 2001 09  37388·
 2001 10  36345.
 2001 11  77376·
 2001 12  52411.
 2002 01 61369.
 2002 02 86405·
 2002 03 93421.
 2002 04 58401·
 2002 05 22437·
 2002 06 61439·
 2002 07 93422·
 2002 08 3397.
 2002 09 95390·
 2002 10 68384.
 2002 11 15372.
 2002 12 55387·
 2003 01  82358.
 2003 02  38379·
 2003 03  22380·
 2003 04  9331.
 2003 05  6340.
 2003 06  29355·
 2003 07  1363.
 2003 08  83375·
 2003 09  19376·
 2003 10  22309·
 2003 11  67306.
 2003 12  21334.
 2004 01 96325·
 2004 02 24315·
 2004 03 56293·
 2004 04 94287·
 2004 05 38321.
 2004 06 66319·
 2004 07 31359·
 2004 08 94385.
 2004 09 69387·
 2004 10 4354.
 2004 11 81357.
 2004 12 42357.
 2005 01  41328·
 2005 02  22295.
 2005 03  18318.
 2005 04  80264.
 2005 05  28287·
 2005 06  24320.
 2005 07  80338.
 2005 08  79349·
 2005 09  31322·
 2005 10  43372.
 2005 11  30388.
 2005 12  33382.
 2006 01 75333·
 2006 02 36329·
 2006 03 56338·
 2006 04 60287.
 2006 05 11320·
 2006 06 84350.
 2006 07 71328·
 2006 08 6332·
 2006 09 14360·
 2006 10 94350·
 2006 11 13346.
 2006 12 38366·
 2007 01  85356·
 2007 02  97361.
 2007 03  44398.
 2007 04  51335·
 2007 05  48408.
 2007 06  50353.
 2007 07  52359.
 2007 08  64347.
 2007 09  55356.
 2007 10  34323.
 2007 11  51318.
 2007 12  22331.
 2008 01 81342.
 2008 02 57348·
 2008 03 78325·
 2008 04 93307·
 2008 05 25345.
 2008 06 50371.
 2008 07 97353.
 2008 08 72305·
 2008 09 14247·
 2008 10 70308·
 2008 11 94281.
 2008 12 78332.
 2009 01  98355·
 2009 02  98350·
 2009 03  84295·
 2009 04  54308.
 2009 05  52273.
 2009 06  41277·
 2009 07  3303.
 2009 08  71307·
 2009 09  77277.
 2009 10  30277·
 2009 11  14290.
 2009 12  22273·
 2010 01 98302·
 2010 02 22295·
 2010 03 7294.
 2010 04 26251.
 2010 05 65265·
 2010 06 99290·
 2010 07 93333·
 2010 08 28339·
 2010 09 54304.
 2010 10 68285.
 2010 11 10271·
 2010 12 96322.
 2011 01  66295·
 2011 02  60326.
 2011 03  22319·
 2011 04  25256.
 2011 05  24277.
 2011 06  31274·
 2011 07  15262.
 2011 08  34254·
 2011 09  81274.
 2011 10  64273.
 2011 11  4293.
 2011 12  67321·
 2012 01 11283·
 2012 02 64342·
 2012 03 26307.
 2012 04 94286·
 2012 05 15290.
 2012 06 65304.
 2012 07 43316.
 2012 08 7297·
 2012 09 19297.
 2012 10 21301·
 2012 11 45278·
 2012 12 27310.
 2013 01  71282.
 2013 02  16302.
 2013 03  43284.
 2013 04  98286.
 2013 05  49296.
 2013 06  55332.
 2013 07  75342·
 2013 08  89320.
 2013 09  52302.
 2013 10  71285.
 2013 11  5259·
 2013 12  93268·
 2014 01 5293·
 2014 02 19269·
 2014 03 20252·
 2014 04 30287.
 2014 05 60253·
 2014 06 81215.
 2014 07 33235.
 2014 08 45242·
 2014 09 91270.
 2014 10 65299·
 2014 11 82292·
 2014 12 6295.
 2015 01  99289.
 2015 02  2331·
 2015 03  31306.
 2015 04  7318.
 2015 05  10284.
 2015 06  48288·
 2015 07  66302.
 2015 08  68264.
 2015 09  73247·
 2015 10  85272·
 2015 11  1314·
 2015 12  33313·
 2016 01 64293·
 2016 02 19312.
 2016 03 73287·
 2016 04 71324.
 2016 05 83282.
 2016 06 84315·
 2016 07 46336.
 2016 08 75338.
 2016 09 57337.
 2016 10 34261.
 2016 11 7278.
 2016 12 66270·
 2017 01  34301.
 2017 02  51306.
 2017 03  70296·
 2017 04  87303·
 2017 05  92319·


 2017 06  43341.
 2017 07  72269.
 2017 08  8274.
 2017 09  29285·
 2017 10  41301.
 2017 11  76332·
 2017 12  22323·
 2018 01 72336.
 2018 02 1317·
 2018 03 70290·
 2018 04 49243.
 2018 05 70319.
 2018 06 5314·
 2018 07 67316·
 2018 08 32319·
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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 in Manufacturing Industry: 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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