Consider the estimator $b_1=\frac{\sum y_i}{\sum x_i}$. Suppose that $y_i = \beta x_i + \epsilon_i$, $E[\epsilon_i]=0$, $E[\epsilon_i \epsilon_j] (i \neq j)$ and $E[\epsilon_i^2]=\sigma_i^2$. Find a model for the variance of $b_1$ for which th estimator is BLUE.
The answer is supposed to be:
$v_i=x_i$ and $\sigma_i^2=\sigma^2 x_i$
However, I am not sure how they got to this answer. Could anyone please help?
Update:
I tried computing the variance of $b_1$. I get:
$$
{\rm Var}(b_1)=\frac 1 {(∑x^2_i)^2}∑x^2_i\ {\rm Var}(\varepsilon_i)
$$
I don't see however how I could proceed from here or whether this was the right thing to do.