04 Jun Question Homework 5. Econ 412 Labor Economics and Labor Markets
Question
Homework 5.
Econ 412 Labor Economics and Labor Markets
Spring 2015
Problem 1
The following problem will ask you to undertake an analysis of gender and race wage gap similar to
the one in O’Neill and O’Neill (2006) study ”What Do Wage Differentials Tell Us about Labor Market
Discrimination?”. Start by downloading data stored in NLSY.dta. This data contains an extract from
National Longitudinal Survey of Youth (NLSY) for year 2000, when people in the sample had reached
ages 35-43. Also download the description of data NLSY.pdf, and if you plan to use R this function for
Oaxaca-Blinder decomposition oaxaca.R
For this HW you have to again submit your solution typed in Word (or LaTeX) and the Word file should
include all graphs and tables based on results from Stata and R. Print it out, but also upload it on ANGEL
together with your Stata or R code.
(a) Create an overlapping density plot (normalized histogram) for: (1) log wage by gender, (2) years of
work by gender, (3) fraction of time worked part time by gender, (4) years of education by gender.
To have nice graphs try changing the number of bins – try 10, 15, 20, 25 bins as alternatives. This is
especially important for years of education, where you should specify the start to be 0 and the number
of bins to be 10.
Hint: in Stata overlapping histograms can be created using
graph twoway
( hist lwage if female==1, bin(15) start(1) lcolor(pink) fcolor(none) )
( hist lwage if female==0, bin(15) start(1) lcolor(eltblue) fcolor(none) ),
ytitle(“density”) xtitle(“log(wage) by gender”) legend(lab(1 “women”) lab(2 “men”))
Hint: in R similar result can be achieved using
hist(log(mydata$wage[mydata$female==0]),breaks=15,freq=FALSE,col=rgb(0,0,1,1/4),
xlab=”log(wage)”,main=”log(wage) by gender”)
hist(log(mydata$wage[mydata$female==1]),breaks=15,freq=FALSE,col=rgb(1,0,0,1/4),add=TRUE)
legend(“topright”,c(“men”, “women”),bty=”n”, fill=c(rgb(0,0,1,1/4),rgb(1,0,0,1/4)))
(b) Comment on differences among men and women in graphs in part (a).
(c) Create the same four overlapping density plots as in (a) but this time by race.
(d) Comment on differences among white and nonwhite in graphs in part (c).
(e) Recall that one reason for transforming variables by taking logarithm is that changes in the logarithm
are (almost) equal to percentage changes in the original data, that is log w2 ? log w1 ?
w2?w1
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