(Solution Library) Suppose data from a large corporation are used to estimate a regression model that explains the corporation's salary structure. The.
Question: Suppose data from a large corporation are used to estimate a regression model that explains the corporation's salary structure. The. estimated equation is
\[\hat{y}_{1}=10,000+1,000 x_{i 1}+1,000 x_{i 2}+3,000 x_{i 3}-2,000 x_{i 4}\]where
\(y_{i}=\) Salary of individual \(i\)
\(x_{i 1}=\) Years of service of individual \(i\)
\[\begin{aligned} &x_{i 2}= \begin{cases}1 & \text { if highest degree is } \mathrm{B} . \mathrm{A} . \text { for individual } i \\ 0 & \text { otherwise }\end{cases} \\ &x_{i 3}= \begin{cases}1 & \text { if individual } i \text { has master's or Ph.D. } \\ 0 & \text { otherwise }\end{cases} \\ &x_{i 4} & = \begin{cases}1 & \text { if individual } i \text { is a female } \\ 0 & \text { male }\end{cases} \end{aligned}\]
- Suppose a female Ph.D. has been employed for 4 years. Predict her salary.
- Suppose a male with no college degree has been employed 5 years. Predict his salary.
- Suppose a new male recruit who has a B.A. is hired. Predict his salary. 2
- What is the difference in starting salaries between a B.A. and a Ph.D. recruit of the same gender?
- Interpret the coefficient of \(x_{i 4}\). How would the coefficient change if we let \(x_{14}\) be 1 for a male and 0 otherwise?
Deliverable: Word Document 
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