Suppose you are interested in predicting CEO salary based on the firms sales volume and its ROE. See file ceo_salary.xls

The definition of the variables of interest is presented in the table below:

Variable	Definition / Unit
salary	CEO salary in U.S dollars
sales	U.S dollar sales volume
roe	Return on equity

Consider the following model:

salaryi= 0+1salesi+2roei+ui

a. Estimate the parameters of this model and write down the equation.

b. Interpret all the parameters estimated in the regression equation

c. Are the coefficients statistically significant? Conduct proper hypothesis testing for each coefficient

d. How well does the estimated regression equation fit the data? Explain the R-squared

e. Plot a scatter plot of the residuals and comment on the result.

f. Plot the squared residuals against the estimated salary from the regression model and comment on the result.

g. Write down the null and the alternative hypothesis to test the homoscedastic assumption of the classical linear regression model.

h. Write down the auxiliary regression equation for the White test to find out if the error variance is homoscedastic (in abstract way, using notations).

i. Conduct White test to test the hypothesis stated in part g.

j. If heteroscedasticity is established, what might you do to correct for this violation of OLS assumptions?

I Want Solution For Part (i) and (j) .