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 Series Title: Employment Level: Farming, Fishing, and Forestry Occupations, Mexican: 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 83447·
 2000 02 7434.
 2000 03 13414.
 2000 04 98491.
 2000 05 83512·
 2000 06 89564.
 2000 07 42576.
 2000 08 96560·
 2000 09 87511·
 2000 10 7398·
 2000 11 9344·
 2000 12 30346·
 2001 01  45367.
 2001 02  43297·
 2001 03  27323.
 2001 04  44433.
 2001 05  33499·
 2001 06  2422.
 2001 07  34343.
 2001 08  7400·
 2001 09  50401.
 2001 10  18396.
 2001 11  94346·
 2001 12  14316.
 2002 01 23306.
 2002 02 46328·
 2002 03 93303.
 2002 04 84427.
 2002 05 2429·
 2002 06 69464.
 2002 07 45551·
 2002 08 61480.
 2002 09 62538·
 2002 10 92470.
 2002 11 88282·
 2002 12 14281·
 2003 01  4285.
 2003 02  48326.
 2003 03  85337.
 2003 04  36326·
 2003 05  53353·
 2003 06  92361.
 2003 07  23407.
 2003 08  49504.
 2003 09  59577·
 2003 10  8528.
 2003 11  16399.
 2003 12  94363.
 2004 01 97323·
 2004 02 1314·
 2004 03 1276.
 2004 04 42339·
 2004 05 69385·
 2004 06 3400.
 2004 07 41398·
 2004 08 87470.
 2004 09 0416.
 2004 10 70341·
 2004 11 24380.
 2004 12 48287.
 2005 01  39275·
 2005 02  85305·
 2005 03  64329·
 2005 04  68336.
 2005 05  63350·
 2005 06  54426·
 2005 07  97450·
 2005 08  18462·
 2005 09  71395.
 2005 10  8373·
 2005 11  87388·
 2005 12  91280.
 2006 01 89276·
 2006 02 5299.
 2006 03 21281.
 2006 04 7364.
 2006 05 68387.
 2006 06 25459·
 2006 07 13465·
 2006 08 9410·
 2006 09 83356·
 2006 10 76341.
 2006 11 1331.
 2006 12 67299.
 2007 01  34322·
 2007 02  89313.
 2007 03  47309·
 2007 04  74324·
 2007 05  47364·
 2007 06  21410·
 2007 07  39463.
 2007 08  51368·
 2007 09  71352.
 2007 10  54358·
 2007 11  90343.
 2007 12  40402.
 2008 01 84406.
 2008 02 93375·
 2008 03 38367·
 2008 04 12371.
 2008 05 84339·
 2008 06 71350.
 2008 07 46340.
 2008 08 61363.
 2008 09 97415·
 2008 10 44355·
 2008 11 2301.
 2008 12 5320·
 2009 01  74277.
 2009 02  95335.
 2009 03  19271.
 2009 04  88351.
 2009 05  89396.
 2009 06  29403.
 2009 07  34402·
 2009 08  80359·
 2009 09  45364.
 2009 10  78366.
 2009 11  10364·
 2009 12  76314.
 2010 01 65282·
 2010 02 99315·
 2010 03 36286·
 2010 04 93347·
 2010 05 0428.
 2010 06 74422.
 2010 07 24478·
 2010 08 77425·
 2010 09 25415·
 2010 10 9452.
 2010 11 13349·
 2010 12 96339.
 2011 01  42328·
 2011 02  35385·
 2011 03  64348·
 2011 04  44352.
 2011 05  75489·
 2011 06  11448.
 2011 07  66502·
 2011 08  42466·
 2011 09  75383.
 2011 10  16372.
 2011 11  32321.
 2011 12  32310·
 2012 01 16326.
 2012 02 58380.
 2012 03 0334.
 2012 04 84337.
 2012 05 1388·
 2012 06 68441.
 2012 07 32468.
 2012 08 92412.
 2012 09 53451.
 2012 10 4416·
 2012 11 17373·
 2012 12 75333.
 2013 01  23290.
 2013 02  46297.
 2013 03  67284.
 2013 04  78316.
 2013 05  88345·
 2013 06  2373·
 2013 07  20409.
 2013 08  69427·
 2013 09  46435.
 2013 10  2438·
 2013 11  40380·
 2013 12  43299·
 2014 01 24331.
 2014 02 4310·
 2014 03 14284.
 2014 04 18353.
 2014 05 71403·
 2014 06 89455.
 2014 07 54448·
 2014 08 40479·
 2014 09 64497·
 2014 10 64458.
 2014 11 99448.
 2014 12 76346·
 2015 01  3389·
 2015 02  61372.
 2015 03  12398.
 2015 04  22410.
 2015 05  12384·
 2015 06  36445.
 2015 07  81454·
 2015 08  96477.
 2015 09  43512·
 2015 10  70483.
 2015 11  18466·
 2015 12  43441.
 2016 01 71412·
 2016 02 71406.
 2016 03 61426.
 2016 04 31402·
 2016 05 96473·
 2016 06 70486.
 2016 07 74481.
 2016 08 55526.
 2016 09 43480.
 2016 10 24429.
 2016 11 44425.
 2016 12 34363·
 2017 01  64381·
 2017 02  14379·
 2017 03  84468·
 2017 04  12443.
 2017 05  33482·
 2017 06  48519.
 2017 07  32495.
 2017 08  59507·
 2017 09  50538·
 2017 10  55547.
 2017 11  51511·


 2017 12  67404.
 2018 01 42378·
 2018 02 94381·
 2018 03 28343·
 2018 04 57323.
 2018 05 58427·
 2018 06 46433.
 2018 07 77553.
 2018 08 73510.
 2018 09 75593.
 2018 10 18549·
 2018 11 36526·
 2018 12 83486.
 2019 01  91458·
 2019 02  41491·
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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

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

Sites of Interest: Conerly Consulting: Economics for Business Decisions *

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