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Basic Question 1 of 6

Suppose data from a large corporation are used to estimate a regression model that explains the corporation's salary structure. The estimated equation is y-hatt = 35,000 + 3,000 xt1 + 6000 xt2 + 15,000 xt3 - 2000 xt4

where

  • y-hatt = salary of individual t.
  • xt1 = years of service of individual t.
  • xt2 = 1 if highest degree is B.A for individual t, or 0 otherwise.
  • xt3 = 1 if individual has master's or Ph.D., or 0 otherwise.
  • xt4 = 1 if individual is a female, or 0 if individual is male.

Question 1: Suppose a female Ph.D. has been employed for 4 years. Predict her salary.
Question 2: Suppose a male with no college degree has been employed 5 years. Predict his salary.
Question 3: Suppose a new male recruit who has a B.A. is hired. Predict his salary.
Question 4: How would these coefficients change if we let xt4 be 1 for a male and 0 otherwise.
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User Contributed Comments 8

User Comment
johans Why would the intercept decrease to 33,000?
webII for Q4 - why would the answer not be holding all other factors equal, the change would now pay a female $2000 more than a male with similar qualifications.
nick1981 Incorrect webli, it would not alter any of the previous assumptions only changing perspective.
xyzanand Meaning that both men and women lose 2000. So if they hire horses, they wont lose the 2000 and if the horse had phd and many years of service he would make even more.
rhardin I still don't understand why the intercept decreased. I also don't understand why the PHD doesn't get credit for having a BA. I thought that was understood... if you have a PHD you have a basic college degree too.
Quinner The point is that they want to know how to change the equation (coefficients) without changing the results. So you have to change the intercept.
andynyc because it would then be +2000 instead of -2000 so to make Yhat the same, intercept falls.
Mckett hardin I thought the same but it states if BA is the highest its 1, if they have a PHD then BA is not highest
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I used your notes and passed ... highly recommended!
Lauren

Lauren

Learning Outcome Statements

formulate and interpret a multiple regression model that includes qualitative independent variables;

CFA® 2025 Level II Curriculum, Volume 1, Module 4.