1. A bit of practice with dummy variables and heteroskedasticity: Consider the following model for the logarithm of wage given years of university education and gender of person i : log (wage;) = Bo + do female; + B, totuni; + 81female; x totuni; + uj (1) where log is the natural logarithm, female; is a dummy variable that is equal to 1 if person i is female is 0 otherwise, and totuni; is the number of years of university education that person i has. Based on a random sample of 6763 individuals, we have estimated this model using OLS and obtained the following estimated equation: log(wage) = 3.289 -0.360 female; + 0.050totuni; + 0.030 female, x totunii, (0.011) (0.015) (0.003) (0.005) 1,2,..., 6763, R2 = 0.202. 1 = (a) Explain how you would test the hypothesis that the conditional expectation of log (wage) conditional on years of university education is exactly the same for men and women. You need to specify the null and the alternative, the test statistic and its distribution under the null, the regression that you should run so that you can compute the test statistic, and the rule for rejection or non- rejection of the null hypothesis. (b) Explain what insights the estimated model reported above provide about the conditional