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Estimating a Wage Equation with Microdata
Load the Excel file CPS85.xls into EViews.
This file is an extract from the 1985 Current Population Survey. It
contains observations on 534 individuals, with measures of hourly earnings,
education, age, and various industry and socio-economic indicators.
To start, generate a new variable that measures the experience of each worker
by subtracting (ED + 6) from the worker's AGE,
where ED is the number of years of education the worker has
completed. Call this new variable EX for experience.
Questions to answer:
- Regress the log of the wage on education and experience.
Interpret the estimated slope coefficients economically.
- Test the null hypothesis that the returns to education
equal the returns to experience. (That is, that an
additional year of either education or experience leads to
the same change in the log wage.)
- Now add the square of education and the square of experience
to the above regression in question (1). Does this specification
"fit" the data better than the original one? Explain.
- Test the null hypothesis that the specification in question (1)
is correct, against the alternative hypothesis represented by
the specification of question (3). Interpret your results.
- According to the results in question (3), what effect does an
additional year of education have on wages? What about an
additional year of experience? Do either of these results
surprise you? Explain.
- Test the null hypothesis that neither education nor education
squared belongs in the regression of question (3). Interpret
your results.
- Explain why it is not possible to estimate a regression equation
with
ED, EX, and AGE included
as regressors.
- What percent of the sample is female? Now add
FE,
a dummy variable that takes on the value 1 if the individual is
female, to the regression in question (3) and re-estimate.
Interpret the economic meaning of the coefficient on
FE.
Does this specification "fit" the data better than the one
in question (3) that did not include this dummy variable?
How does including this dummy variable change your answers
to question (4), if at all?
- Describe how you would test whether the returns to schooling
and to experience differed between males and females in this
sample. Be explicit.
Extra Credit: Use this sample to implement the test you
just described, and provide an economic interpretation of your
results.
Comments:
- You may discuss this problem set with your classmates,
but do your own work. Submitting any part of another student's
work as your own is a violation of the
Honor Code
and is not acceptable.
- Print your name and Wes ID number on each page you submit. You
should place all of the written answers on one page. (If you
want to place more than one graph on a page, you may do that
as well.)
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