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 Series Title: Employment Level: Farming, Fishing, and Forestry Occupations, Mexican: NSA
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 2000 01 53447·
 2000 02 77434·
 2000 03 53414·
 2000 04 36491·
 2000 05 1512·
 2000 06 27564·
 2000 07 95576.
 2000 08 17560.
 2000 09 83511·
 2000 10 44398·
 2000 11 7344.
 2000 12 66346.
 2001 01  52367.
 2001 02  10297.
 2001 03  1323.
 2001 04  26433·
 2001 05  81499.
 2001 06  32422·
 2001 07  15343·
 2001 08  67400·
 2001 09  71401·
 2001 10  41396.
 2001 11  13346·
 2001 12  83316·
 2002 01 49306·
 2002 02 93328·
 2002 03 82303.
 2002 04 92427.
 2002 05 63429.
 2002 06 71464.
 2002 07 35551·
 2002 08 40480.
 2002 09 89538.
 2002 10 81470.
 2002 11 10282·
 2002 12 95281·
 2003 01  29285·
 2003 02  55326.
 2003 03  70337·
 2003 04  52326·
 2003 05  6353.
 2003 06  49361.
 2003 07  3407.
 2003 08  29504·
 2003 09  73577·
 2003 10  45528·
 2003 11  22399·
 2003 12  71363·
 2004 01 3323·
 2004 02 50314·
 2004 03 64276.
 2004 04 46339·
 2004 05 98385·
 2004 06 95400.
 2004 07 92398.
 2004 08 50470.
 2004 09 82416.
 2004 10 37341.
 2004 11 95380·
 2004 12 0287·
 2005 01  7275.
 2005 02  57305·
 2005 03  85329.
 2005 04  42336·
 2005 05  47350·
 2005 06  63426·
 2005 07  1450·
 2005 08  45462·
 2005 09  3395·
 2005 10  85373.
 2005 11  4388·
 2005 12  1280·
 2006 01 0276·
 2006 02 81299·
 2006 03 83281.
 2006 04 32364.
 2006 05 89387.
 2006 06 32459·
 2006 07 51465.
 2006 08 80410·
 2006 09 46356.
 2006 10 45341·
 2006 11 46331.
 2006 12 15299.
 2007 01  69322.
 2007 02  51313.
 2007 03  30309.
 2007 04  31324.
 2007 05  86364·
 2007 06  7410·
 2007 07  92463.
 2007 08  48368.
 2007 09  46352·
 2007 10  95358.
 2007 11  44343.
 2007 12  9402·
 2008 01 25406.
 2008 02 21375.
 2008 03 24367.
 2008 04 83371·
 2008 05 22339·
 2008 06 17350.
 2008 07 96340·
 2008 08 65363·
 2008 09 65415.
 2008 10 40355·
 2008 11 46301·
 2008 12 74320·
 2009 01  2277.
 2009 02  71335.
 2009 03  88271·
 2009 04  54351·
 2009 05  9396.
 2009 06  17403.
 2009 07  61402.
 2009 08  74359·
 2009 09  87364·
 2009 10  9366.
 2009 11  26364·
 2009 12  28314.
 2010 01 61282·
 2010 02 4315.
 2010 03 71286·
 2010 04 35347.
 2010 05 81428·
 2010 06 85422·
 2010 07 10478.
 2010 08 40425·
 2010 09 23415·
 2010 10 56452.
 2010 11 81349.
 2010 12 11339·
 2011 01  88328.
 2011 02  51385·
 2011 03  45348·
 2011 04  43352.
 2011 05  0489·
 2011 06  26448.
 2011 07  92502.
 2011 08  56466·
 2011 09  10383.
 2011 10  62372.
 2011 11  34321.
 2011 12  92310.
 2012 01 93326·
 2012 02 65380.
 2012 03 9334·
 2012 04 21337·
 2012 05 50388.
 2012 06 69441·
 2012 07 80468.
 2012 08 38412.
 2012 09 6451·
 2012 10 29416·
 2012 11 34373.
 2012 12 61333·
 2013 01  12290·
 2013 02  26297·
 2013 03  85284·
 2013 04  35316.
 2013 05  43345·
 2013 06  69373·
 2013 07  71409.
 2013 08  29427.
 2013 09  99435·
 2013 10  87438·
 2013 11  53380·
 2013 12  36299·
 2014 01 6331·
 2014 02 39310.
 2014 03 22284.
 2014 04 77353.
 2014 05 13403·
 2014 06 4455.
 2014 07 88448·
 2014 08 95479.
 2014 09 98497·
 2014 10 91458·
 2014 11 90448.
 2014 12 59346.
 2015 01  59389.
 2015 02  31372.
 2015 03  92398·
 2015 04  63410.
 2015 05  22384·
 2015 06  80445·
 2015 07  80454.
 2015 08  27477·
 2015 09  39512.
 2015 10  20483·
 2015 11  68466.
 2015 12  95441·
 2016 01 83412.
 2016 02 58406.
 2016 03 94426·
 2016 04 36402.
 2016 05 56473.
 2016 06 25486·
 2016 07 20481·
 2016 08 44526·
 2016 09 82480.
 2016 10 78429.
 2016 11 34425·
 2016 12 37363.
 2017 01  13381·
 2017 02  99379·
 2017 03  50468.
 2017 04  62443·
 2017 05  23482.
 2017 06  94519.


 2017 07  5495·
 2017 08  85507·
 2017 09  14538.
 2017 10  95547·
 2017 11  62511.
 2017 12  3404·
 2018 01 9378·
 2018 02 58381.
 2018 03 9343·
 2018 04 33323.
 2018 05 61427.
 2018 06 66433·
 2018 07 59553.
 2018 08 19510.
 2018 09 44593·
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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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