Assignment # 2
Submission due: February 26th 2021 (Friday); 12:00NN.
Direction: Answer all the questions and submit your exercise in PDF. Make sure to include your
R scripts or computer codes as an appendix to your submission (You can copy your codes from
the R script and paste them on the MS Word document). Please comment on each procedure so
I would know what you are doing (or intend to do). In your write up, be explicit in your
assumptions. Submission is via E-BART.
1. For this section, you will use the CPS1985 dataset in the “AER” package. The dataset is a
cross-section data originating from the May 1985 Current Population Survey by the US
Census Bureau (random sample drawn for Berndt (1991)1
. Install the package “AER” if you
have not done so and load it in your library. Then load the dataset “CPS1985”. Answer the
following question. Make sure you include all your regression results in here (leave the
codes in the appendix).
a. Plot the wage (in US dollars per hour) on experience (Number of years of potential
work experience (age – year of education -6). What relationship do you observe? Is
the relationship sensible? Please briefly explain. (10 points)
b. Run a regression of wage on experience (that is, estimate wagei = αi +
β1Experience + ui). What values for the slope and the intercept would you expect?
Interpret the coefficients, the R
2 and the Standard Error of Regression (SER) in the
resulting regression output (state clearly the unit of measurement). (15 points)
c. In your plot in (a), do you observe an outlier in terms of wage? If yes, remove the
outlier by creating another dataset that does not include the outlier. (Hint: you can
use the subset() function for this step). Re-estimate wagei = αi + β1Experience + ui
on the new dataset. What do you observe in terms of the coefficients and measures
of fit? What can you conclude from this exercise? (10 points)
d. Run a regression of wage on education and calculate homoskedastic-only standard
errors. Using the procedure in the lecture, run a regression of wage on education and
calculate heteroskedastic-robust standard errors. Compare the standard errors.
Which one is larger? What can you conclude from this exercise? (15 points)
2. Using the CPS1985 dataset in (1), you will investigate the relationship between hourly wage
a. In the sample, calculate the following:
i. Average value of hourly wage rate for all individuals? (Hint: you can use the
mean() function for this question. For example, the mean of age for
1 Berndt, E.R. (1991). The Practice of Econometrics. New York: Addison-Wesley.
individuals with 10 years of work experience can be calculated by
mean(CPS1985$age[CPS1985$experience==10]). (5 points)
ii. Average value of hourly wage rate for females. (2.5 points)
iii. Average value of hourly wage rate for males (2.5 points)
iv. Calculate the standard error for the estimated difference. (Hint: you can use
the sd() function which is analogous to mean() function). (5 points)
b. Perform the following:
i. Using the same sample, estimate the difference in average wage between
male and female. (5 points)
ii. Calculate the standard error for the estimated difference in the average
hourly wage for the estimated difference in b(i). (5 points)
iii. Construct a 95% confidence interval for the difference in the average hourly
wage between male and female respondents. (5 points)
c. Run a regression of wage on the binary variable gender.
i. Explain how the estimated slope and intercept are related to your answer in
parts (a) and (b). (5 points)
ii. Explain how the SE(β̂) is related to your answer in b(ii). (5 points)
iii. What can you conclude from this exercise? (Hint: You need to perform
hypothesis testing based on the regression result). (10 points)
Such a cheap price for your free time and healthy sleep
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