Please answer question 4-6 CLEARLY. Thank you!

(30 points) A study of the "gender gap" in earnings in top corporate jobs compares total compensation among top executives in a large set of U.S public corporation in the 1990s. Let Female be an indicator variable that is equal to 1 for females and 0 otherwise. A regression of the logarithm of earning onto females yields ln(Earnings)=6.480.44Female(0.01)(0.05)SSR=11.4R2=.32 1. The estimated coefficient on females is 0.44. Explain what this value means. 2. Does this regression suggest that there is gender discrimination? Explain. 3. Another researcher uses the same data used to produce the regression output 6.1, but regresses log of Earnings on Male, a variable that is equal to 1 if the person is male and zero otherwise. What are the regression estimates calculated from this new regression? ln(Earnings)=+Male,R2=,SSR= Two new variables, the market value of the firm (a measure of firm size in millions of dollars) and stock return (a measure of the firm performance in percentage points), are added to the regression: ln(Earnings)=3.860.28Female+0.37ln(MarketValue)+0.004Return(0.03)(0.04)(0.004)n=46,670,R2=0.345 4. The coefficient on ln (MarketValue) is 0.37. Explain what this value means. 5. The coefficient on Female is now 0.28. Explain why it has changed from the previous regression. 6. Given the outcome of your regression, are large firms more likely to have female top executives than small firms? Explain