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 Series Title: Employment Level: Agriculture and Related Industries, Unpaid Family Workers, 65 years and over, Men: NSA
   For this series:   Numerical Data  |  Forecast  |  GIF Chart  |  PDF Chart  |  Excel file  |  Self-updating Excel file
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 2012 04 843·
 2012 03 960·
 2012 02 100·
 2012 01 840·
 2011 12  31·
 2011 11  500.
 2011 10  130·
 2011 09  9
 2011 08  371.
 2011 07  511.
 2011 06  674·
 2011 05  834.
 2011 04  383·
 2011 03  833·
 2011 02  840·
 2011 01  500.
 2010 12 822·
 2010 11 522.
 2010 10 42·
 2010 09 780.
 2010 08 680·
 2010 07 890.
 2010 06 873·
 2010 05 633.
 2010 04 214·
 2010 03 515·
 2010 02 240.
 2010 01 230.
 2009 12  940.
 2009 11  200.
 2009 10  250.
 2009 09  20.
 2009 08  590·
 2009 07  20.
 2009 06  300.
 2008 12 70
 2008 11 191·
 2008 09 291·
 2008 08 11.
 2008 01 202·
 2007 12  982·
 2007 11  572.
 2007 10  271·
 2007 09  720·
 2007 08  480·
 2007 07  692.
 2007 06  192·
 2007 05  70
 2007 04  421.
 2007 03  710·
 2006 04 151.
 2006 03 841.
 2006 02 82
 2006 01 940.
 2005 11  800.
 2005 09  62·
 2005 08  932.
 2005 07  952.
 2005 06  00·
 2005 05  570·
 2004 08 261.
 2004 07 561·
 2004 04 891.
 2003 09  802·
 2003 06  551.
 2003 05  842.
 2003 01  842.
 2002 12 452·
 2002 11 812·
 2002 10 103.
 2002 05 482.
 2001 09  450.
 2001 08  300·
 2001 07  900.
 2001 06  700.
 2001 05  16.
 2001 01  52
 2000 11 72.
 2000 09 612·
 2000 08 562.
 2000 06 23
 2000 05 663·
 2000 04 613·
 2000 03 78
 1999 10  422.
 1999 06  13.
 1999 04  311.
 1998 11 633.
 1998 10 353.
 1998 06 663.
 1998 05 603·
 1998 04 303.
 1998 01 533·
 1997 12  453.
 1997 11  603.
 1997 10  223.
 1997 09  712·
 1997 08  432.
 1997 07  713·
 1997 06  90·
 1997 05  892·
 1997 04  922.
 1997 03  532.
 1997 02  853·
 1997 01  334·
 1996 12 503.
 1996 11 96
 1996 10 698·
 1996 09 531.
 1996 08 961.
 1996 07 121.
 1996 06 51·
 1996 05 251.
 1996 04 390·
 1996 03 390·
 1996 02 620·
 1996 01 480·
 1995 12  10
 1995 11  401·
 1995 10  353·
 1995 09  493·
 1995 08  653.
 1995 07  33·
 1995 06  434.
 1995 05  774·
 1995 04  862·
 1995 03  402.
 1995 02  290·
 1995 01  80·
 1994 12 791.
 1994 11 912·
 1994 10 63
 1994 09 433.
 1994 08 776·
 1994 07 164.
 1994 06 393.
 1994 05 71.
 1994 04 360.
 1994 03 52·
 1994 02 764·
 1994 01 494·
 1993 12  382.
 1993 11  715.
 1993 10  1910·
 1993 08  475.
 1993 07  894.
 1993 06  503·
 1993 05  368.
 1993 04  991.
 1993 03  202.
 1993 02  76.
 1993 01  227.
 1992 12 325.
 1992 11 909.
 1992 10 297·
 1992 09 956.
 1992 08 961·
 1992 07 785·
 1992 06 286.
 1992 05 0
 1992 04 661.
 1992 02 923.
 1991 11  444·
 1991 10  66·
 1991 09  421·
 1991 08  644.
 1991 07  388·
 1991 06  8
 1991 05  516.
 1991 04  50
 1991 03  985·
 1991 02  232·
 1991 01  415.
 1990 12 315·
 1990 11 386.
 1990 10 977.
 1990 09 909·
 1990 08 157·
 1990 07 9511.
 1990 06 995.
 1990 05 973·
 1990 04 335.
 1990 03 332·
 1990 02 221.
 1990 01 873·
 1989 12  422.
 1989 11  383.
 1989 10  875.
 1989 09  116.
 1989 08  237.
 1989 07  257.
 1989 06  369·
 1989 05  449.
 1989 04  824·
 1989 03  307·
 1989 01  393·
 1988 12 871.
 1988 11 534.
 1988 10 1710·
 1988 09 919·
 1988 08 656·
 1988 07 9011.
 1988 06 749.
 1988 05 102·
 1988 03 2910.
 1988 02 772.
 1988 01 134·
 1987 12  403·
 1987 11  547.
 1987 10  198·
 1987 09  7313·
 1987 08  5212·
 1987 07  3918·
 1987 06  4813·
 1987 05  166·
 1987 04  383·
 1987 03  124.
 1987 02  212.
 1987 01  312.
 1986 12 184·
 1986 11 2113.
 1986 10 195.
 1986 09 2915.
 1986 08 3617·
 1986 07 438.
 1986 06 4912·
 1986 05 498.
 1986 04 614·
 1986 03 784·
 1986 02 443·
 1986 01 551.
 1985 12  8814·
 1985 11  512.
 1985 10  586.
 1985 09  339·
 1985 08  365.
 1985 07  1311·
 1985 06  744·
 1985 05  976.
 1985 04  4810.
 1985 03  385·
 1985 02  994·
 1985 01  846·
 1984 12 944.
 1984 11 287·
 1984 10 656·
 1984 09 5810.
 1984 08 679.
 1984 07 85.
 1984 06 276.
 1984 05 68.
 1984 04 885·
 1984 03 284.
 1984 02 682·
 1984 01 422.
 1983 12  03.
 1983 11  63
 1983 10  935·
 1983 09  24·
 1983 08  735.
 1983 07  14
 1983 06  369.
 1983 05  519.
 1983 04  04·
 1983 03  73·
 1983 02  521·
 1983 01  75
 1982 12 12.
 1982 11 923.
 1982 10 248·
 1982 09 895.
 1982 08 195.
 1982 07 437.
 1982 06 574.
 1982 05 298·
 1982 04 254·
 1982 03 626.
 1982 02 833·
 1982 01 586.
 1981 12  126.
 1981 11  743.
 1981 10  60
 1981 09  655·
 1981 08  985.
 1981 07  306.
 1981 06  685.
 1981 05  624.
 1981 04  302.
 1981 03  49.
 1981 02  144·
 1981 01  881·
 1980 12 7411.
 1980 11 976·
 1980 10 3110.
 1980 09 54·
 1980 08 27
 1980 07 346.
 1980 06 748·
 1980 05 111.
 1980 04 64·
 1980 03 663.
 1980 02 256·
 1980 01 881·
 1979 11  564.
 1979 10  693.
 1979 09  912·
 1979 08  67·
 1979 07  464.
 1979 06  421.
 1979 05  46.
 1979 04  167·
 1979 03  701.
 1979 02  122·
 1979 01  201.
 1978 12 72.
 1978 11 482.
 1978 10 277·
 1978 09 204.
 1978 08 928.
 1978 07 231.
 1978 06 656.
 1978 05 129·
 1978 04 7
 1978 03 6510.
 1978 02 24
 1977 12  271·
 1977 10  1710·
 1977 09  676·
 1977 08  324.
 1977 07  2213.
 1977 06  99·
 1977 05  509·
 1977 04  375·
 1977 03  781·
 1977 02  975.
 1977 01  5610·
 1976 12 16
 1976 11 36·
 1976 10 175.
 1976 09 566·
 1976 08 683·
 1976 07 266.
 1976 06 33
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US Unemployment Rate: Alternative Measures of Labor Underutilization

Charts

Unemployment Rate: US Unemployment Rate: 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: Agriculture and Related Industries, Unpaid Family Workers, 65 years and over, Men: 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

Make charts for Okun's Law and Phillip's Curve

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