Suppose that the regression model is y i = + x i + i ,
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Suppose that the regression model is yi = α + βxi + εi, where the disturbances εi have f (εi) = (1/λ) exp(−εi /λ), εi ≥ 0. This model is rather peculiar in that all the disturbances are assumed to be nonnegative. 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.
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We could write the regression as y i b x i i x i i Then we know that E ...View the full answer
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