Refer to the U S savingsincome regression discussed in the chapter As analternative to Eq (9 5 1), consider the following model ln Y t 1 2 D t 3 X t 4 (D t X t ) u t where Y is savings and X is income a Estimate the preceding model and compare the results with those given in Eq (9 5 4) Which is a b...

The results using EViews are as follows Variable Coefficient Std Error tStatistic Prob C 3677198 0108486 3389569 00000 INCOME 0000709 780E05 9084319 0 ...

Refer to the U.S. savingsincome regression discussed in the chapter. As analternative to Eq. (9.5.1), consider the

Question:

Refer to the U.S. savings–income regression discussed in the chapter. As analternative to Eq. (9.5.1), consider the following model:

ln Y_t = β₁ + β₂D_t + β₃X_t + β₄(D_t X_t ) + u_t

where Y is savings and X is income.

a. Estimate the preceding model and compare the results with those given in Eq. (9.5.4). Which is a better model?

b. How would you interpret the dummy coefficient in this model?

c. As we will see in the chapter on heteroscedasticity, very often a log transformation of the dependent variable reduces heteroscedasticity in the data. See if this is the case in the present example by running the regression of log of Y on X for the two periods and see if the estimated error variances in the two periods are statistically the same. If they are, the Chow test can be used to pool the data in the manner indicated in the chapter.