Answer the question 11-15.
Population Survey
Each month the Bureau of Labor Statistics in the U.S. Department of Labor conducts the “Current Population Survey” (CPS), which provides data on labour force characteristics of the population, including the level of employment, unemployment, and earnings. Approximately 65,000 randomly selected U.S. households are surveyed each month. The sample is chosen by randomly selecting addresses from a database comprised of addresses from the most recent decennial census augmented with data on new housing units constructed after the last census. The exact random sampling scheme is rather complicated (first small geographical areas are randomly selected, then housing units within these areas randomly selected).
The file Assignment Data.xlsx, tab: Young Workers Survey contains the data from the survey. These data are for full-time workers, defined as workers employed more than 35 hours per week for at least 48 weeks in the previous year. Data are provided for workers whose highest educational achievement is (1) a high school diploma, and (2) a bachelor’s degree.
Series in Data Set:
FEMALE: 1 if female; 0 if male
YEAR: Year
AHE : Average Hourly Earnings
BACHELOR: 1 if worker has a bachelor’s degree; 0 if worker has a high school degree
Use the data in Assignment Data.xlsx, tab: Young Workers Survey to answer the following questions:
C11. (1 mark) Plot the regression relation between Age and ln(AHE) from C5, C6, and C7 for males with a high school diploma. Describe the similarities and differences between the estimated regression functions. Would you answer change if you plotted the regression function for females with college degrees?
C12. (1 mark) Run a regression of ln(AHE), on Age, Age2, Female, Bachelor, and the interaction term FemaleBachelor. What does the coefficient on the interaction term measure? Alexis is a 30-year-old female with a bachelor’s degree. What does the regression predict for her value of ln(AHE)? Jane is a 30-year-old female with a high school degree. What does the regression
predict for her value of ln(AHE)? What is the predicted difference between Alexis’s and Jane’s earnings? Bob is a 30-year-old male with a bachelor’s degree. What does the regression predict for his value of ln(AHE)? Jim is a 30-year-old male with a high school degree. What does the regression predict for his value of ln(AHE)? What is the predicted difference between Bob’s
and Jim’s earnings?
C13. (1 mark) Is the effect of Age on earnings different for men than for women? Specify and estimate a regression that you can use to answer this question.
C14. (1 mark) Is the effect of Age on earnings different for high school graduates than for college graduates? Specify and estimate a regression that you can use to answer this question.
C15. (1 mark) After running all these regressions (and any others that you want to run), summarize the effect of age on earnings for young workers.
The following is the part of C5,6,7 required for C11
C5. (1 mark) Run a regression of the logarithm of average hourly earnings, ln(AHE) on Age, gender (Female), and education (Bachelor). Report Excel/Matlab output. What is the estimated effect of Age on earnings? What is the estimated effect of Age on earnings? If Age increases from 25 to 26, how are earnings expected to change? If Age increases from 33 to 34, how are earnings expected to change?
SE: (0.077) (0.015) (0.015) (0.003)
– 0.025
If Age increases from 25 to 26, the earnings expected to increase 0.025 dollars per year.
– 0.025
If Age increases from 33 to 34, the earnings expected to increase 0.025 dollars per year.
From the equation above, only one data changes if other data remains unchanged. Then the data of this change can give the final answer whether it is increasing or decreasing.
C6. (1 mark) Run a regression of the logarithm of average hourly earnings, ln(AHE) on ln(Age), gender (Female), and education (Bachelor). Report Excel/Matlab output. What is the estimated effect of Age on earnings? What is the estimated effect of Age on earnings? If Age increases from 25 to 26, how are earnings expected to change? If Age increases from 33 to 34, how are earnings expected to change?
SE: (0.257) (0.015) (0.015) (0.076)
|Ln(Age) 26 – 0.738
If Age increases from 25 to 26, the earnings expected to increase 0.738 dollars per year.
|Ln(Age) 34 – 0.738
If Age increases from 33 to 34, the earnings expected to increase 0.738 dollars per year.
From the equation above, only one data changes if other data remains unchanged. Then the data of this change can give the final answer whether it is increasing or decreasing.
C7. (1 mark) Run a regression of the logarithm of average hourly earnings, ln(AHE) on Age, Age2, gender (Female), and education (Bachelor). Report Excel/Matlab output. What is the estimated effect of Age on earnings? What is the estimated effect of Age on earnings? If Age increases from 25 to 26, how are earnings expected to change? If Age increases from 33 to 34, how are earnings expected to change?
=1.756 + 0.442 *Bachelor + (-0.154) * Female+ 0.021 *Age + 6.43262E-05
SE: (0.877) (0.015) (0.015) (0.060) (0.001)
= when Age is 25 = 1.756 + 0.442 *Bachelor + (-0.154) * Female+ 0.021 *25 + 6.43262E-05
= when Age is 26 = 1.756 + 0.442 *Bachelor + (-0.154) * Female+ 0.021 *26 + 6.43262E-05
0.021
If Age increases from 25 to 26, the earnings expected to increase 0.021 dollars per year.
= when Age is 33 = 1.756 + 0.442 *Bachelor + (-0.154) * Female+ 0.021 *33 + 6.43262E-05
= when Age is 34 = 1.756 + 0.442 *Bachelor + (-0.154) * Female+ 0.021 *34 + 6.43262E-05
0.021
If Age increases from 33 to 43, the earnings expected to increase 0.021 dollars per year.
From the equation above, only one data changes if other data remains unchanged. Then the data of this change can give the final answer whether it is increasing or decreasing.
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