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 Series Title: Employment Level: Farming, Fishing, and Forestry Occupations in Wholesale Trade 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 8171·
 2000 02 3760.
 2000 03 4065·
 2000 04 4271·
 2000 05 21107.
 2000 06 54109·
 2000 07 2490.
 2000 08 41107·
 2000 09 9678·
 2000 10 3951·
 2000 11 7870·
 2000 12 667.
 2001 01  5659·
 2001 02  7267.
 2001 03  1485·
 2001 04  8485.
 2001 05  7897·
 2001 06  61106·
 2001 07  7076·
 2001 08  4281.
 2001 09  6086·
 2001 10  3773.
 2001 11  1077.
 2001 12  7578·
 2002 01 3056·
 2002 02 5763·
 2002 03 2261.
 2002 04 266·
 2002 05 3684.
 2002 06 271·
 2002 07 1763·
 2002 08 6781.
 2002 09 5594.
 2002 10 7976·
 2002 11 3462·
 2002 12 3954.
 2003 01  8664.
 2003 02  2070·
 2003 03  3749.
 2003 04  1334.
 2003 05  5633·
 2003 06  8123.
 2003 07  1233·
 2003 08  735·
 2003 09  1547·
 2003 10  4445·
 2003 11  7242.
 2003 12  6642.
 2004 01 3738.
 2004 02 1671·
 2004 03 5759·
 2004 04 5960.
 2004 05 2462.
 2004 06 2870.
 2004 07 2748·
 2004 08 8057.
 2004 09 060.
 2004 10 3842.
 2004 11 7255·
 2004 12 4755.
 2005 01  1741.
 2005 02  2544.
 2005 03  540.
 2005 04  636·
 2005 05  5032.
 2005 06  9843.
 2005 07  6237.
 2005 08  2637.
 2005 09  9863.
 2005 10  8870.
 2005 11  864.
 2005 12  064·
 2006 01 8758.
 2006 02 5168.
 2006 03 2953·
 2006 04 4846.
 2006 05 6953.
 2006 06 6959.
 2006 07 3934·
 2006 08 1331.
 2006 09 1747·
 2006 10 4947·
 2006 11 7647.
 2006 12 6549.
 2007 01  3337.
 2007 02  2232.
 2007 03  242.
 2007 04  9942·
 2007 05  4240·
 2007 06  4545·
 2007 07  660.
 2007 08  3253·
 2007 09  9453.
 2007 10  058·
 2007 11  143·
 2007 12  1158·
 2008 01 6567.
 2008 02 9459.
 2008 03 2347·
 2008 04 232.
 2008 05 5531·
 2008 06 5727·
 2008 07 3727.
 2008 08 130·
 2008 09 8940·
 2008 10 4751.
 2008 11 2944.
 2008 12 2741·
 2009 01  1941·
 2009 02  4542.
 2009 03  1445·
 2009 04  2441·
 2009 05  1832.
 2009 06  5840.
 2009 07  2833.
 2009 08  6130·
 2009 09  8832.
 2009 10  1846.
 2009 11  3651.
 2009 12  3243·
 2010 01 5447·
 2010 02 8060.
 2010 03 2354.
 2010 04 5757.
 2010 05 6737·
 2010 06 2846.
 2010 07 546·
 2010 08 7958.
 2010 09 164.
 2010 10 6752.
 2010 11 1757·
 2010 12 6857.
 2011 01  5872.
 2011 02  2967.
 2011 03  2459.
 2011 04  1772.
 2011 05  6255.
 2011 06  7034·
 2011 07  1345.
 2011 08  4624.
 2011 09  6429·
 2011 10  7336·
 2011 11  9745.
 2011 12  047.
 2012 01 4043·
 2012 02 4547·
 2012 03 1435.
 2012 04 4655·
 2012 05 8962·
 2012 06 1560.
 2012 07 2774.
 2012 08 8041·
 2012 09 3753.
 2012 10 4245.
 2012 11 2441.
 2012 12 2132·
 2013 01  3529.
 2013 02  731·
 2013 03  1733.
 2013 04  1232·
 2013 05  5845.
 2013 06  1751·
 2013 07  4553·
 2013 08  2353.
 2013 09  635·
 2013 10  238.
 2013 11  7027.
 2013 12  4719·
 2014 01 529·
 2014 02 2142.
 2014 03 8031.
 2014 04 544·
 2014 05 551.
 2014 06 5452·
 2014 07 8947·
 2014 08 4049·
 2014 09 8239·
 2014 10 827.
 2014 11 3337·
 2014 12 2142.
 2015 01  3569·
 2015 02  1560·
 2015 03  7745.
 2015 04  4346.
 2015 05  9157.
 2015 06  3149·
 2015 07  764·
 2015 08  2453·
 2015 09  9947.
 2015 10  3846·
 2015 11  3736·
 2015 12  949.
 2016 01 3632·
 2016 02 4330.
 2016 03 527.
 2016 04 6745.
 2016 05 138·
 2016 06 7838·
 2016 07 7332·
 2016 08 9234·
 2016 09 1933.
 2016 10 9825.
 2016 11 3037·
 2016 12 333·
 2017 01  4239.
 2017 02  8658.
 2017 03  8863·
 2017 04  4556·
 2017 05  4556.
 2017 06  4862·


 2017 07  8547·
 2017 08  8529.
 2017 09  2732·
 2017 10  1647.
 2017 11  8573·
 2017 12  2057.
 2018 01 1544.
 2018 02 4741·
 2018 03 7410·
 2018 04 6738·
 2018 05 5942.
 2018 06 2233·
 2018 07 6640.
 2018 08 7127.
 2018 09 3425·
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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 Wholesale Trade 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

New data set: Quarterly Financial Reporting: Manufacturing, Mining, Trade, and Selected Service Industries

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