Important: Please use datafile CPS18.2.csv to complete this assignment. A description of this data may be found in Documentation for CPS18.2 Data.docx. Make sure that you generate heteroske dasticity robust standard errors for all regressions. If you are using SPSS to complete this assignment, that will probably mean installing the RLM macro (see macro-spss.pdf for installation instructions).
In this exercise, you will investigate the relationship between a worker’s experience and annual earnings (generally, more job experience leads to higher productivity and higher earnings). Please answer all questions in full sentences and create ONE table (see page 287 in Stock & Watson for an example) with all regressions in the end.
a.Run a regression of average annual earnings (AAE) on experience, gender and education.
If experience increases from 25 to 26, how are earnings expected to change?
If experience increases from 33 to 34, how are earnings expected to change?
b.Run a regression of the logarithm of AAE, ln(AAE), on experience, gender and education.
If experience increases from 25 to 26, how are earnings expected to change?
If experience increases from 33 to 34, how are earnings expected to change?c.Run a regression of the logarithm of AAE, ln(AAE), on ln(experience), gender and education.
If experience increases from 25 to 26, how are earnings expected to change?
If experience increases from 33 to 34, how are earnings expected to change?d.Run a regression of the logarithm of AAE, ln(AAE), on experience, , gender and education.
If experience increases from 25 to 26, how are earnings expected to change?
If experience increases from 33 to 34, how are earnings expected to change?e.Do you prefer the regression in
(c) to the regression in (b)? Explain.
.Do you prefer the regression in (d) to the regression in (b)? Explain.
g.Do you prefer the regression in (d) to the regression in (c)? Explain.
h.Run a regression of ln(AAE) on experience, , gender, education and the interaction term female x Bachelor.
What does the coefficient on the interaction term measure?
Alexis (female) has 30 years of experience and a bachelor’s degree. What does the regression predict for her value of the ln(AAE)?
Jane (female) has 30 years of experience and a high school diploma. What does the regression predict for her value of the ln(AAE)?
What is the predicted difference between Alexi’s and Jane’s earnings?
Bob (male) has 30 years of experience and a bachelor’s degree. What does the regression predict for his value of the ln(AAE)?
Jimmy (male) has 30 years of experience and a high school diploma. What does the regression predict for his value of the ln(AAE)?
What is the predicted difference between Bob’s and Jimmy’s earnings?
i.Is the effect of experience on earnings different for men than for women? Specify and estimate a regression that you can used to answer this question.
j.Is the effect of experience on earnings different for high school graduates than for college graduates? Specify and estimate a regression that you can used to answer this question.
k.After running all these regressions (and any others that you want to run), summarize the effect of experience on earnings for young workers (given that younger workers have less experience).