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Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Bachelor's degree and higher: 25 years and over (LEU0252918500A)

Observation:

2016: 1,259  
Updated: Jan 24, 2017

Units:

Dollars,
Not Seasonally Adjusted

Frequency:

Annual
1Y | 5Y | 10Y | Max
  EDIT BAR 1
(a) Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Bachelor's degree and higher: 25 years and over, Dollars, Not Seasonally Adjusted (LEU0252918500A)
Data measure usual weekly earnings of wage and salary workers. Wage and salary workers are workers who receive wages, salaries, commissions, tips, payment in kind, or piece rates. The group includes employees in both the private and public sectors but, for the purposes of the earnings series, it excludes all self-employed persons, both those with incorporated businesses and those with unincorporated businesses.
Usual weekly earnings represent earnings before taxes and other deductions and include any overtime pay, commissions, or tips usually received (at the main job in the case of multiple jobholders). Prior to 1994, respondents were asked how much they usually earned per week. Since January 1994, respondents have been asked to identify the easiest way for them to report earnings (hourly, weekly, biweekly, twice monthly, monthly, annually, or other) and how much they usually earn in the reported time period. Earnings reported on a basis other than weekly are converted to a weekly equivalent. The term "usual" is determined by each respondent's own understanding of the term. If the respondent asks for a definition of "usual," interviewers are instructed to define the term as more than half the weeks worked during the past 4 or 5 months. For more information see http://www.bls.gov/cps/earnings.htm

The series comes from the 'Current Population Survey (Household Survey)'

The source code is: LEU0252918500

Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Bachelor's degree and higher: 25 years and over

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  EDIT BAR 2
(a) Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Bachelor's degree and higher: 25 years and over, Dollars, Not Seasonally Adjusted (LEU0252918500A)
Data measure usual weekly earnings of wage and salary workers. Wage and salary workers are workers who receive wages, salaries, commissions, tips, payment in kind, or piece rates. The group includes employees in both the private and public sectors but, for the purposes of the earnings series, it excludes all self-employed persons, both those with incorporated businesses and those with unincorporated businesses.
Usual weekly earnings represent earnings before taxes and other deductions and include any overtime pay, commissions, or tips usually received (at the main job in the case of multiple jobholders). Prior to 1994, respondents were asked how much they usually earned per week. Since January 1994, respondents have been asked to identify the easiest way for them to report earnings (hourly, weekly, biweekly, twice monthly, monthly, annually, or other) and how much they usually earn in the reported time period. Earnings reported on a basis other than weekly are converted to a weekly equivalent. The term "usual" is determined by each respondent's own understanding of the term. If the respondent asks for a definition of "usual," interviewers are instructed to define the term as more than half the weeks worked during the past 4 or 5 months. For more information see http://www.bls.gov/cps/earnings.htm

The series comes from the 'Current Population Survey (Household Survey)'

The source code is: LEU0252918500

Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Bachelor's degree and higher: 25 years and over

Select a date that will equal 100 for your custom index:
to

Customize data:

Write a custom formula to transform one or more series or combine two or more series.

You can begin by adding a series to combine with your existing series.

Now create a custom formula to combine or transform the series.
Need help? []

Finally, you can change the units of your new series.

Select a date that will equal 100 for your custom index:

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Log scale:

NOTES
Title Release Dates

2015-01-21 2017-01-24
 
Source    

2015-01-21 2017-01-24
 
Release    

2015-01-21 2017-01-24
 
Units    

2015-01-21 2017-01-24
 
Frequency    

2015-01-21 2017-01-24
 
Seasonal Adjustment    

2015-01-21 2017-01-24
 
Notes    

2015-01-21 2017-01-24





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