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 Series Title: Employment Level: Farming, Fishing, and Forestry Occupations in Manufacturing Industry: NSA
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 2012 04 3158.
 2012 03 764.
 2012 02 8467.
 2012 01 9060.
 2011 12  7753·
 2011 11  9959·
 2011 10  1149·
 2011 09  153·
 2011 08  3338.
 2011 07  3351.
 2011 06  8360·
 2011 05  5440.
 2011 04  4941·
 2011 03  9145·
 2011 02  1367.
 2011 01  9357.
 2010 12 269·
 2010 11 7966.
 2010 10 3868·
 2010 09 8857.
 2010 08 9042·
 2010 07 3053·
 2010 06 2164·
 2010 05 3371.
 2010 04 4074·
 2010 03 9952·
 2010 02 5153.
 2010 01 4741.
 2009 12  349.
 2009 11  6967·
 2009 10  4043·
 2009 09  7540·
 2009 08  5232·
 2009 07  4635.
 2009 06  2529.
 2009 05  8430.
 2009 04  9045·
 2009 03  6141·
 2009 02  7148·
 2009 01  7053.
 2008 12 4042.
 2008 11 7263·
 2008 10 6453·
 2008 09 5155·
 2008 08 5555.
 2008 07 6038·
 2008 06 1842.
 2008 05 7249.
 2008 04 855.
 2008 03 3245.
 2008 02 7140·
 2008 01 243·
 2007 12  148.
 2007 11  1855.
 2007 10  8578·
 2007 09  3570.
 2007 08  5881·
 2007 07  7782·
 2007 06  4965·
 2007 05  9073.
 2007 04  3161.
 2007 03  8951.
 2007 02  7464·
 2007 01  1151.
 2006 12 9443·
 2006 11 6253·
 2006 10 056·
 2006 09 6855·
 2006 08 4852.
 2006 07 2651.
 2006 06 8936.
 2006 05 5439.
 2006 04 1839.
 2006 03 3953·
 2006 02 2867.
 2006 01 8864·
 2005 12  5672·
 2005 11  8179.
 2005 10  3270·
 2005 09  1675·
 2005 08  3555.
 2005 07  6156.
 2005 06  3764·
 2005 05  588.
 2005 04  5771·
 2005 03  950.
 2005 02  750.
 2005 01  5141.
 2004 12 4756.
 2004 11 8258.
 2004 10 2949·
 2004 09 7263·
 2004 08 5570.
 2004 07 6169·
 2004 06 1769.
 2004 05 1256·
 2004 04 5644.
 2004 03 5445.
 2004 02 850.
 2004 01 4163·
 2003 12  5262·
 2003 11  9262.
 2003 10  6570.
 2003 09  5266·
 2003 08  6762·
 2003 07  3245.
 2003 06  7655·
 2003 05  6558·
 2003 04  5254.
 2003 03  5583.
 2003 02  5481·
 2003 01  2465·
 2002 12 8366·
 2002 11 6745.
 2002 10 3735.
 2002 09 9840·
 2002 08 5949·
 2002 07 149·
 2002 06 8773.
 2002 05 8158.
 2002 04 656·
 2002 03 1450·
 2002 02 9352·
 2002 01 9362.
 2001 12  7466·
 2001 11  8661·
 2001 10  6854·
 2001 09  7750·
 2001 08  3964.
 2001 07  2451·
 2001 06  4951·
 2001 05  36.
 2001 04  214.
 2001 03  6119·
 2001 02  9922·
 2001 01  6525·
 2000 12 8723·
 2000 11 5216.
 2000 10 69·
 2000 09 812·
 2000 08 454.
 2000 07 8016·
 2000 06 8420.
 2000 05 9718.
 2000 04 5122.
 2000 03 5011.
 2000 02 6915.
 2000 01 8047.
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US Unemployment Rate: Alternative Measures of Labor Underutilization

Charts

Unemployment Rate: US Unemployment Rate: 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 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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