Question: (Two-Step Estimation) Suppose that $E[y_n | X_n] = X_n beta_0$ and $Var(y_n | X_n) = sigma^2_n (X_n beta)^2$, so that the conditional variance of $y_n$

(Two-Step Estimation) Suppose that $E[y_n | X_n] = X_n \beta_0$ and $Var(y_n | X_n) = \sigma^2_n (X_n \beta)^2$, so that the conditional variance of $y_n$ increases with the magnitude of its conditional mean. Also suppose that conditional on $\{X_n\}$, the $\{y_n\}$ are independent and normally distributed. Describe an efficient two-step estimator of $\beta_0$ and show thereby that FGLS is relatively inefficient. Explain the source of inefficiency.**

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