Parade Magazine 2005 Earnings Data

Description

US earnings data, as provided in an annual survey of Parade (here from 2005), the Sunday newspaper magazine supplementing the Sunday (or Weekend) edition of many daily newspapers in the USA.

Usage

data("Parade2005")

Format

A data frame containing 130 observations on 5 variables.

earnings

Annual personal earnings.

age

Age in years.

gender

Factor indicating gender.

state

Factor indicating state.

celebrity

Factor. Is the individual a celebrity?

Details

In addition to the four variables provided by Parade (earnings, age, gender, and state), a fifth variable was introduced, the “celebrity factor” (here actors, athletes, TV personalities, politicians, and CEOs are considered celebrities). The data are quite far from a simple random sample, there being substantial oversampling of celebrities.

Source

Parade (2005). What People Earn. Issue March 13, 2005.

Examples

## data
data("Parade2005")
attach(Parade2005)
summary(Parade2005)

## bivariate visualizations
plot(density(log(earnings), bw = "SJ"), type = "l", main = "log(earnings)")
rug(log(earnings))
plot(log(earnings) ~ gender, main = "log(earnings)")

## celebrity vs. non-celebrity earnings
noncel <- subset(Parade2005, celebrity == "no")
cel <- subset(Parade2005, celebrity == "yes")

library("ineq")
plot(Lc(noncel$earnings), main = "log(earnings)")
lines(Lc(cel$earnings), lty = 2)
lines(Lc(earnings), lty = 3)

Gini(noncel$earnings)
Gini(cel$earnings)
Gini(earnings)

## detach data
detach(Parade2005)

Results

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> library(AER)
Loading required package: car
Loading required package: lmtest
Loading required package: zoo

Attaching package: 'zoo'

The following objects are masked from 'package:base':

    as.Date, as.Date.numeric

Loading required package: sandwich
Loading required package: survival
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/AER/Parade2005.Rd_%03d_medium.png", width=480, height=480)
> ### Name: Parade2005
> ### Title: Parade Magazine 2005 Earnings Data
> ### Aliases: Parade2005
> ### Keywords: datasets
> 
> ### ** Examples
> 
> ## data
> data("Parade2005")
> attach(Parade2005)
> summary(Parade2005)
    earnings             age           gender       state    celebrity
 Min.   :   10000   Min.   :18.00   female:62   CA     :10   no :119  
 1st Qu.:   30000   1st Qu.:30.25   male  :68   ID     : 5   yes: 11  
 Median :   50000   Median :38.50               IN     : 5            
 Mean   : 1503412   Mean   :39.18               VA     : 5            
 3rd Qu.:   78575   3rd Qu.:47.00               FL     : 4            
 Max.   :42000000   Max.   :64.00               IL     : 4            
                                                (Other):97            
> 
> ## bivariate visualizations
> plot(density(log(earnings), bw = "SJ"), type = "l", main = "log(earnings)")
> rug(log(earnings))
> plot(log(earnings) ~ gender, main = "log(earnings)")
> 
> ## celebrity vs. non-celebrity earnings
> noncel <- subset(Parade2005, celebrity == "no")
> cel <- subset(Parade2005, celebrity == "yes")
> 
> library("ineq")
> plot(Lc(noncel$earnings), main = "log(earnings)")
> lines(Lc(cel$earnings), lty = 2)
> lines(Lc(earnings), lty = 3)
> 
> Gini(noncel$earnings)
[1] 0.3814012
> Gini(cel$earnings)
[1] 0.38754
> Gini(earnings)
[1] 0.9228179
> 
> ## detach data
> detach(Parade2005)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>