Study the determinants of house prices. Collecte a dataset with 43 observations in the same town in the South of California, which includes the following variables

P: the price (in thousands of dollars) of the house.

S: the size (in square feet) of the house

N: the quality of the neighbourhood where the house (1=best; 4= worst) as rated by two local estate agents.

CA: dummy variable equal to 1 if the house has central air conditioning, 0 otherwise.

Y: the size of the garden (in square feet).

A: age of the house.

The estimation results that you are asked to consider are in table 1 (computed with EViews):

Table 1 

1. What is the interpretation of the coefficient on CA? Is its sign consistent with your expectations?

2. Test the individual significance of the coefficient of CA against the alternative that it is positive. Use a 5% significance level.

3. What is the effect of the size of the house on its price? Discuss.

4. What is the effect of the age of the house on its price? Discuss.

5. Calculate the goodness of fit of the equation in table 1. Discuss.      

6. Test the overall significance of the coefficients. Use a 1% significance level.   

7. You are asked to test whether there is heteroskedasticity in this dataset using the Breusch-Pagan test.

a. Specify the auxiliary regression and the null and alternative hypotheses of this test.

b. The results of running this test with EViews are provided in table 2. Is there evidence of heteroskedasticity in this dataset? Justify your answer.     

Table 2