Consider the following earnings function: ahe Bo+B1xDFemme + B2 educ+...+ u versus the alternative specification ahe-...

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Consider the following earnings function: ahe Bo+B1xDFemme + B2 educ+...+ u versus the alternative specification ahe- yox DMale+ yDFemme + 2educ+...+ u where ahe is average hourly earnings, DFemme is a binary variable which takes on the value of "1" if the individual is a female and is "0" otherwise, educ measures the years of education, and DMale is a binary variable which takes on the value of "1" if the individual is a male and is "0" otherwise. There may be additional explanatory variables in the equation. Answer the following questions: a. How do the s and ys compare? Putting it differently, having estimated the coefficients in the first equation, can you derive the coefficients in the second equation without re-estimating the regression? (5%) b. Will the goodness of fit measures, such as the regression R2, differ between the two equations? (5%) c. Looking at both equations, what are they estimating differently? (5%) Consider the following earnings function: ahe Bo+B1xDFemme + B2 educ+...+ u versus the alternative specification ahe- yox DMale+ yDFemme + 2educ+...+ u where ahe is average hourly earnings, DFemme is a binary variable which takes on the value of "1" if the individual is a female and is "0" otherwise, educ measures the years of education, and DMale is a binary variable which takes on the value of "1" if the individual is a male and is "0" otherwise. There may be additional explanatory variables in the equation. Answer the following questions: a. How do the s and ys compare? Putting it differently, having estimated the coefficients in the first equation, can you derive the coefficients in the second equation without re-estimating the regression? (5%) b. Will the goodness of fit measures, such as the regression R2, differ between the two equations? (5%) c. Looking at both equations, what are they estimating differently? (5%)