Suppose that you are trying to model the determinants of high infant mortality.You have data at the county level about the infant mortality rate (Infant), per capita income (Income), and the number of doctors per 100,000 people (Docs) from 102 urban counties in the United States.Suppose that you want to choose between the linear and log-log functional forms for the regression:

= 1 + 2 + 3 +

ln() = 1 + 2 ln() + 3 ln() +

You estimate each regression and perform the MacKinnon-White-Davidson test.The test regressions are:

= 1 + 2 + 3 + 41, +

ln() = 1 + 2 ln() + 3 ln() + 52, + 1, = ln( ) 2, = exp( ) : :ln()

You obtain the following parameter estimates from the test regressions: 4 = 17.626;(4 ) = 12.472 5 = 0.239;(5 ) = 0.039 Does the test indicate that you should prefer the linear or the log-log model?If so, which one should you prefer?Please show your work.