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 Series Title: Employment Level: Farming, Fishing, and Forestry Occupations, Mexican: NSA
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 2000 01 3447.
 2000 02 83434.
 2000 03 70414.
 2000 04 33491.
 2000 05 69512.
 2000 06 76564.
 2000 07 53576.
 2000 08 29560·
 2000 09 15511·
 2000 10 79398·
 2000 11 49344.
 2000 12 36346·
 2001 01  90367·
 2001 02  76297.
 2001 03  71323·
 2001 04  98433.
 2001 05  70499·
 2001 06  71422.
 2001 07  58343·
 2001 08  84400.
 2001 09  54401.
 2001 10  97396.
 2001 11  72346.
 2001 12  89316·
 2002 01 69306·
 2002 02 11328.
 2002 03 0303·
 2002 04 32427.
 2002 05 65429·
 2002 06 94464.
 2002 07 57551.
 2002 08 57480.
 2002 09 17538·
 2002 10 53470.
 2002 11 79282.
 2002 12 33281·
 2003 01  25285·
 2003 02  19326·
 2003 03  30337·
 2003 04  54326.
 2003 05  15353·
 2003 06  49361.
 2003 07  98407·
 2003 08  39504·
 2003 09  38577.
 2003 10  25528.
 2003 11  95399·
 2003 12  32363·
 2004 01 69323.
 2004 02 54314.
 2004 03 59276·
 2004 04 4339.
 2004 05 7385.
 2004 06 66400·
 2004 07 53398·
 2004 08 46470·
 2004 09 80416.
 2004 10 19341.
 2004 11 66380.
 2004 12 80287·
 2005 01  36275·
 2005 02  95305.
 2005 03  9329·
 2005 04  49336·
 2005 05  51350·
 2005 06  99426·
 2005 07  22450.
 2005 08  22462·
 2005 09  26395·
 2005 10  64373.
 2005 11  66388·
 2005 12  93280·
 2006 01 87276.
 2006 02 46299·
 2006 03 30281.
 2006 04 81364·
 2006 05 82387·
 2006 06 27459·
 2006 07 26465.
 2006 08 31410.
 2006 09 89356.
 2006 10 14341.
 2006 11 93331.
 2006 12 12299.
 2007 01  7322.
 2007 02  37313.
 2007 03  93309·
 2007 04  18324·
 2007 05  61364·
 2007 06  55410·
 2007 07  14463.
 2007 08  68368·
 2007 09  3352·
 2007 10  47358.
 2007 11  70343·
 2007 12  5402.
 2008 01 7406.
 2008 02 22375.
 2008 03 97367.
 2008 04 0371·
 2008 05 73339.
 2008 06 11350·
 2008 07 60340.
 2008 08 47363.
 2008 09 28415.
 2008 10 70355.
 2008 11 45301.
 2008 12 63320·
 2009 01  22277·
 2009 02  81335.
 2009 03  66271·
 2009 04  95351.
 2009 05  29396.
 2009 06  50403.
 2009 07  60402·
 2009 08  10359·
 2009 09  51364·
 2009 10  10366.
 2009 11  91364·
 2009 12  4314.
 2010 01 13282.
 2010 02 17315.
 2010 03 46286·
 2010 04 94347·
 2010 05 65428·
 2010 06 52422·
 2010 07 39478.
 2010 08 26425·
 2010 09 83415·
 2010 10 23452.
 2010 11 6349·
 2010 12 68339·
 2011 01  66328·
 2011 02  60385.
 2011 03  12348·
 2011 04  15352.
 2011 05  41489·
 2011 06  21448.
 2011 07  44502.
 2011 08  85466·
 2011 09  57383.
 2011 10  86372·
 2011 11  14321.
 2011 12  23310.
 2012 01 91326.
 2012 02 64380.
 2012 03 61334·
 2012 04 98337·
 2012 05 42388·
 2012 06 85441.
 2012 07 47468·
 2012 08 4412·
 2012 09 36451·
 2012 10 6416·
 2012 11 62373.
 2012 12 61333.
 2013 01  23290.
 2013 02  9297.
 2013 03  16284.
 2013 04  11316·
 2013 05  79345.
 2013 06  0373.
 2013 07  49409·
 2013 08  26427·
 2013 09  4435·
 2013 10  11438·
 2013 11  22380.
 2013 12  97299.
 2014 01 24331.
 2014 02 98310·
 2014 03 25284·
 2014 04 46353.
 2014 05 88403.
 2014 06 44455·
 2014 07 70448·
 2014 08 16479.
 2014 09 73497.
 2014 10 55458·
 2014 11 95448·
 2014 12 75346.
 2015 01  78389·
 2015 02  62372.
 2015 03  62398·
 2015 04  19410·
 2015 05  30384·
 2015 06  22445.
 2015 07  60454.
 2015 08  66477·
 2015 09  77512·
 2015 10  17483·
 2015 11  1466·
 2015 12  61441·
 2016 01 97412·
 2016 02 54406·
 2016 03 24426·
 2016 04 72402·
 2016 05 89473.
 2016 06 63486.
 2016 07 91481·
 2016 08 94526.
 2016 09 78480·
 2016 10 3429·
 2016 11 90425·
 2016 12 46363·
 2017 01  15381.
 2017 02  54379.
 2017 03  34468.
 2017 04  73443·


 2017 05  76482.
 2017 06  22519.
 2017 07  62495·
 2017 08  42507.
 2017 09  60538.
 2017 10  41547.
 2017 11  35511·
 2017 12  48404.
 2018 01 94378.
 2018 02 65381·
 2018 03 41343.
 2018 04 11323.
 2018 05 27427·
 2018 06 78433.
 2018 07 95553·
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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, 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

Unemployment data for every county in the U.S..
Click for Illinois counties, then follow the example for your state

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