University of California, Santa Barbara
Olivier Deschenes
Department of Economics
Winter 2011
____________________________________________________________________________
Economics 140B
Individual Assignment 3
Due in class 02/15/11
Question 1:
The standard model for estimating the return to education is the loglinear wage equation:
(1)
i
2
i
2
i
1
i
1
0
i
u
EXP
γ
EXP
γ
ED
β
β
y
where y
i
is the log hourly wage of worker i, ED
i
is years of education, and EXP
i
is the labor
market experience (measured in years).
This equation is often called the “Mincer equation” in
honor of the labor economist Jacob Mincer, who pioneered its usage.
Since actual labor market
experience is rarely measured in data sets, labor economists proxy it with “years of potential
labor market experience” (defined as ageeducation6).
While potential experience is an error
ridden measure of true labor market experience, we will ignore this issue in this exercise.
The parameter of central interest is
1
, which is interpreted as the “return to education” (since it
measure the percent increase in hourly wages associated with an additional year of education).
Note that we typically include other variables in the Mincer equation (e.g., sex, race, marital
status, etc).
A major concern in the estimation of equation (1) is the presence of omitted
variables that are correlated with both education and wages.
Labor economists often refer to
such omitted variables as “ability”, and the resulting bias in the OLS estimates as the “ability
bias”.
In this exercise, you will investigate different approaches to resolve the ability bias problem,
using two different data sets.
The description and questions related to the first data set follow
immediately in “Part I”, while the description and questions related to the second data set are in
“Part II” at the end.
PART I
The first approach is to include “proxy” measures of ability directly in the wage equation and to
make use of panel data on wages and education of workers, and use fixed and random effect
models to account for unobserved ability.
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 Winter '08
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 Economics, Random effects model, Jacob Mincer, log hourly wage

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