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 Series Title: Employment Level: Farming, Fishing, and Forestry Occupations in Durable Goods Manufacturing Industry: NSA
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 2000 01 156.
 2000 02 802·
 2000 03 974.
 2000 04 249.
 2000 05 468·
 2000 06 4613.
 2000 07 1212·
 2000 08 622·
 2000 09 932·
 2000 10 607.
 2000 11 796.
 2000 12 4810.
 2001 01  716.
 2001 02  516.
 2001 03  910.
 2001 04  277·
 2001 05  621·
 2001 06  861·
 2001 07  404·
 2001 08  686.
 2001 09  614.
 2001 10  352·
 2001 11  373.
 2001 12  66
 2002 01 275.
 2002 02 102.
 2002 03 864.
 2002 04 388.
 2002 05 1210.
 2002 06 9110.
 2002 07 0
 2002 08 303.
 2002 09 907.
 2002 10 8516.
 2002 11 1718.
 2002 12 1018.
 2003 01  6215·
 2003 02  2514.
 2003 03  110.
 2003 04  733·
 2003 05  542·
 2003 06  667.
 2003 07  3810.
 2003 08  3712.
 2003 09  168.
 2003 10  909.
 2003 11  435.
 2003 12  489.
 2004 01 2311.
 2004 02 49.
 2004 03 526.
 2004 04 746.
 2004 05 758.
 2004 06 4026.
 2004 07 2928·
 2004 08 921·
 2004 09 9918.
 2004 10 545·
 2004 11 62
 2004 12 729.
 2005 01  4414.
 2005 02  2819·
 2005 03  6316·
 2005 04  727·
 2005 05  8622.
 2005 06  6815·
 2005 07  7114·
 2005 08  8521.
 2005 09  2519·
 2005 10  615.
 2005 11  489.
 2005 12  984.
 2006 01 865·
 2006 02 997.
 2006 03 82
 2006 04 664.
 2006 05 215·
 2006 06 286·
 2006 07 86
 2006 08 335·
 2006 09 49.
 2006 10 08·
 2006 11 978·
 2006 12 689·
 2007 01  355.
 2007 02  471.
 2007 03  804·
 2007 04  6610·
 2007 05  4124·
 2007 06  2523·
 2007 07  2220·
 2007 08  4513·
 2007 09  717·
 2007 10  1613.
 2007 11  3511.
 2007 12  504.
 2008 01 20.
 2008 02 274.
 2008 03 579.
 2008 04 4911.
 2008 05 328·
 2008 06 896.
 2008 07 5310.
 2008 08 38
 2008 09 894·
 2008 10 589.
 2008 11 810.
 2008 12 34
 2009 01  216·
 2009 02  188·
 2009 03  363·
 2009 04  834·
 2009 05  57.
 2009 06  734.
 2009 07  764·
 2009 08  520·
 2009 09  410·
 2009 10  560·
 2009 11  8917·
 2009 12  386.
 2010 01 549.
 2010 02 23
 2010 03 654.
 2010 04 5813.
 2010 05 956·
 2010 06 571.
 2010 07 154.
 2010 08 573·
 2010 09 394.
 2010 10 635·
 2010 11 773.
 2010 12 34.
 2011 01  863·
 2011 02  742.
 2011 03  169.
 2011 04  9213·
 2011 05  6210·
 2011 06  456.
 2011 07  173.
 2011 08  413.
 2011 09  180.
 2011 10  594.
 2011 11  95
 2011 12  975·
 2012 01 282.
 2012 02 22
 2012 03 875·
 2012 04 260.
 2012 05 937.
 2012 06 677·
 2012 07 577·
 2012 08 2410·
 2012 09 387·
 2012 10 486·
 2012 11 917·
 2012 12 1016·
 2013 01  148·
 2013 02  4913.
 2013 03  37.
 2013 04  286·
 2013 05  966·
 2013 06  76
 2013 07  316.
 2013 08  4613.
 2013 09  856.
 2013 10  602.
 2013 11  3714·
 2013 12  606·
 2014 01 610.
 2014 02 5914·
 2014 03 103.
 2014 04 8810·
 2014 05 106·
 2014 06 539.
 2014 07 629.
 2014 08 7512·
 2014 09 7110.
 2014 10 496·
 2014 11 326.
 2014 12 892.
 2015 01  904.
 2015 02  80
 2015 03  821.
 2015 04  251.
 2015 05  920.
 2015 06  10·
 2015 07  03.
 2015 08  24·
 2015 09  2910.
 2015 10  943.
 2015 11  9910.
 2015 12  637·
 2016 01 7511.
 2016 02 667.
 2016 03 174.
 2016 04 790.
 2016 05 304·
 2016 06 494.
 2016 07 17
 2016 08 435.
 2016 09 215·
 2016 10 996.
 2016 11 8611·
 2016 12 758·
 2017 01  976·
 2017 02  98


 2017 03  3811.
 2017 04  187.
 2017 05  343.
 2017 06  537.
 2017 07  105·
 2017 08  425·
 2017 09  335.
 2017 10  942.
 2017 11  660.
 2017 12  404.
 2018 01 185·
 2018 02 80
 2018 03 924.
 2018 04 339.
 2018 05 402.
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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: Farming, Fishing, and Forestry Occupations in Durable Goods 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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