Regression and Other Stories: Earnings

Bootstrapping to simulate the sampling distribution. See Chapter 5 in Regression and Other Stories.

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Load packages

library("rprojroot")
root<-has_file(".ROS-Examples-root")$make_fix_file()

Load data

earnings <- read.csv(root("Earnings/data","earnings.csv"))
head(earnings)

  height weight male  earn earnk ethnicity education mother_education
1     74    210    1 50000    50     White        16               16
2     66    125    0 60000    60     White        16               16
3     64    126    0 30000    30     White        16               16
4     65    200    0 25000    25     White        17               17
5     63    110    0 50000    50     Other        16               16
6     68    165    0 62000    62     Black        18               18
  father_education walk exercise smokenow tense angry age
1               16    3        3        2     0     0  45
2               16    6        5        1     0     0  58
3               16    8        1        2     1     1  29
4               NA    8        1        2     0     0  57
5               16    5        6        2     0     0  91
6               18    1        1        2     2     2  54

Median of women's earnings, divided by the median of men's earnings

earn <- earnings$earn
male <- earnings$male
print(median(earn[male==0]) / median(earn[male==1]))

[1] 0.6

A single bootstrap sample

n <- nrow(earnings)
boot <- sample(n, replace=TRUE)
earn_boot <- earn[boot]
male_boot <- male[boot]
ratio_boot <- median(earn_boot[male_boot==0]) / median(earn_boot[male_boot==1])

A set of bootstrap simulations

Boot_ratio <- function(data){
  n <- nrow(data)
  boot <- sample(n, replace=TRUE)
  earn_boot <- data$earn[boot]
  male_boot <- data$male[boot]
  ratio_boot <- median(earn_boot[male_boot==0]) / median(earn_boot[male_boot==1])
  return(ratio_boot)
}
n_sims <- 10000
output <- replicate(n_sims, Boot_ratio(data=earnings))

Summarize the results graphically and numerically

hist(output)

round(sd(output), 2)

[1] 0.03