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Unformatted text preview: E[ ε t ] = 0 for all t, x t is I(0), and y t is I(0). a. Suppose the variance of ε t equals σ t 2 . What difficulties characterize statistical hypothesis tests based on OLS estimators of β = ( β , β 1 ′ ) ′ ? b. How would you test for heteroskedasticity of the form σ t 2 = σ 2 z t , where z t are known? Show that the variance of the OLS estimator is higher than the variance of the generalized least squares (GLS) estimator obtained after the appropriate transformation. Are the GLS estimators unbiased? c. Describe the pattern of data associated with heteroskedasticity of the form σ 2 = δ 0 + δ 1 ε t1 2 . How would you estimate the parameters ( β′ , δ , δ 1 )? d. How would you test for heteroskedasticity of the form σ δ δε t t 2 1 1 2 = +?...
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This note was uploaded on 12/26/2011 for the course ECON 245b taught by Professor Staff during the Fall '08 term at UCSB.
 Fall '08
 Staff
 Economics

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