Suppose you are interested in predicting the abortion rate in the USA based on various factors in the excel file Abortion.xls

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

Variable	Definition / Unit
abortion	Abortion rate
price	The average price charged in non-hospital facilities for an abortion
income	Disposable income per capita
law	Enforced law that restricts a minor?s access to abortion,
educ	The percent of a state?s population that is 25 years or older with a high school degree

1. Formulate a multiple linear regression model that includes all potential explanatory variables and estimate it with the given sample data. Hint: Note the presence of a qualitative variable that needs to be re-coded as a dummy variable.

2. Interpret the parameters estimated in the regression equation

3. Are the coefficients statistically significant? *Hint: Conduct proper hypothesis testing

4. How well does the estimated regression equation fit the data? Hint: Explain the R-squared

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

6. Write the auxiliary regression equation for the White test to find out if the error variance is homoscedastic

7. Conduct White test to test the hypothesis stated in part e.

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

Consider the following model: abortioni- Bo + Biprice; + Brincomei + P3 lawi + Beduci + Ui