2. Heteroskedasticity and WLS Suppose we have a regression model with n samples of i.i.d. data where Euxi = 0, Var[ui xi, zi] = independent each other). Yi = ẞxi + ui 2z, and u u; for all i j (i.e. they are (a) Obtain the OLS estimator BOLS for ẞ (b) Obtain the optimal WLS estimator BWLS for ẞ (c) Obtain the variance of the WLS estimator BWLS in part (b) (d) Explain why the WLS estimator is preferred to the OLS estimator in terms of efficiency. In other words, why does the Gauss-Markov theorem hold for the WLS?