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 Series Title: Employment Level: Farming, Fishing, and Forestry Occupations, Mexican: NSA
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 2000 01 80447·
 2000 02 85434.
 2000 03 85414.
 2000 04 12491·
 2000 05 26512.
 2000 06 85564·
 2000 07 53576.
 2000 08 21560.
 2000 09 63511·
 2000 10 8398.
 2000 11 47344.
 2000 12 54346·
 2001 01  42367·
 2001 02  37297·
 2001 03  80323·
 2001 04  55433·
 2001 05  38499·
 2001 06  77422.
 2001 07  89343.
 2001 08  92400.
 2001 09  52401.
 2001 10  60396.
 2001 11  38346.
 2001 12  61316.
 2002 01 8306·
 2002 02 44328.
 2002 03 15303.
 2002 04 80427·
 2002 05 58429·
 2002 06 9464·
 2002 07 32551.
 2002 08 93480.
 2002 09 76538.
 2002 10 62470·
 2002 11 27282·
 2002 12 69281·
 2003 01  64285·
 2003 02  36326·
 2003 03  63337.
 2003 04  4326.
 2003 05  46353.
 2003 06  86361·
 2003 07  29407·
 2003 08  15504.
 2003 09  73577·
 2003 10  94528·
 2003 11  36399.
 2003 12  47363.
 2004 01 20323·
 2004 02 67314·
 2004 03 23276.
 2004 04 69339.
 2004 05 88385·
 2004 06 37400·
 2004 07 53398·
 2004 08 76470.
 2004 09 2416.
 2004 10 60341·
 2004 11 13380.
 2004 12 85287·
 2005 01  12275·
 2005 02  17305.
 2005 03  17329·
 2005 04  42336.
 2005 05  94350·
 2005 06  17426·
 2005 07  2450·
 2005 08  16462·
 2005 09  48395·
 2005 10  89373.
 2005 11  32388.
 2005 12  1280.
 2006 01 0276·
 2006 02 91299·
 2006 03 94281.
 2006 04 15364.
 2006 05 0387·
 2006 06 4459·
 2006 07 0465.
 2006 08 4410·
 2006 09 23356·
 2006 10 35341·
 2006 11 90331.
 2006 12 36299·
 2007 01  70322·
 2007 02  16313·
 2007 03  26309.
 2007 04  5324·
 2007 05  66364.
 2007 06  3410.
 2007 07  95463.
 2007 08  30368·
 2007 09  61352·
 2007 10  78358.
 2007 11  11343.
 2007 12  57402.
 2008 01 32406·
 2008 02 48375.
 2008 03 11367·
 2008 04 53371·
 2008 05 78339.
 2008 06 43350.
 2008 07 59340.
 2008 08 12363.
 2008 09 24415·
 2008 10 22355·
 2008 11 42301.
 2008 12 55320.
 2009 01  22277.
 2009 02  65335·
 2009 03  73271·
 2009 04  25351.
 2009 05  46396·
 2009 06  80403.
 2009 07  90402·
 2009 08  92359.
 2009 09  97364.
 2009 10  97366·
 2009 11  56364·
 2009 12  49314.
 2010 01 1282.
 2010 02 73315.
 2010 03 59286·
 2010 04 15347·
 2010 05 7428.
 2010 06 90422·
 2010 07 12478.
 2010 08 35425.
 2010 09 91415.
 2010 10 56452·
 2010 11 53349.
 2010 12 78339·
 2011 01  53328.
 2011 02  0385.
 2011 03  44348.
 2011 04  38352.
 2011 05  20489.
 2011 06  81448·
 2011 07  73502·
 2011 08  35466.
 2011 09  40383.
 2011 10  79372·
 2011 11  54321.
 2011 12  11310.
 2012 01 91326·
 2012 02 1380·
 2012 03 24334·
 2012 04 37337.
 2012 05 71388.
 2012 06 79441·
 2012 07 46468.
 2012 08 7412.
 2012 09 6451.
 2012 10 70416·
 2012 11 7373.
 2012 12 39333.
 2013 01  48290·
 2013 02  55297.
 2013 03  22284·
 2013 04  78316·
 2013 05  70345.
 2013 06  41373.
 2013 07  28409·
 2013 08  94427.
 2013 09  75435·
 2013 10  59438.
 2013 11  87380.
 2013 12  79299.
 2014 01 86331.
 2014 02 66310.
 2014 03 88284.
 2014 04 53353·
 2014 05 54403.
 2014 06 44455.
 2014 07 43448·
 2014 08 62479.
 2014 09 55497·
 2014 10 0458·
 2014 11 90448·
 2014 12 72346·
 2015 01  90389·
 2015 02  64372·
 2015 03  93398.
 2015 04  79410.
 2015 05  83384.
 2015 06  94445·
 2015 07  39454.
 2015 08  3477.
 2015 09  85512.
 2015 10  71483.
 2015 11  40466.
 2015 12  86441·
 2016 01 71412.
 2016 02 3406·
 2016 03 36426.
 2016 04 98402.
 2016 05 42473·
 2016 06 19486·
 2016 07 88481·
 2016 08 34526·
 2016 09 22480.
 2016 10 79429.
 2016 11 85425.
 2016 12 12363·
 2017 01  64381·
 2017 02  61379·
 2017 03  40468·
 2017 04  76443·
 2017 05  41482.
 2017 06  75519.
 2017 07  90495·
 2017 08  97507.


 2017 09  55538·
 2017 10  51547·
 2017 11  98511.
 2017 12  67404·
 2018 01 30378·
 2018 02 45381·
 2018 03 53343·
 2018 04 6323·
 2018 05 17427·
 2018 06 40433·
 2018 07 67553·
 2018 08 58510.
 2018 09 92593.
 2018 10 41549·
 2018 11 77526·
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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

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