Suppose that the regression model is yi = + xi + i, where the disturbances i have f (i) = (1/) exp (i), i

Suppose that the regression model is yi = α + βxi + εi, where the disturbances εi have f (εi) = (1/λ) exp (−λεi), εi ≥ 0. This model is rather peculiar in that all the disturbances are assumed to be positive. Note that the disturbances have E[εi | xi] = λ and Var[εi | xi] = λ2. Show that the least squares slope is unbiased but that the intercept is biased.