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1 Key Answers for Exercise 2: Q1: (1) Do not agree (DNA). When important regressors are omitted, OLS estimator becomes inconsistent. (2) DNA. As long as WIC hold and T is large, OLS is consistent and asymptotically normal. (3) DNA. Dropping regressors may cause omitted-variables biases. (4) DNA. We can estimate the OLS covariance matrix using the Newey-West method. With this covariance matrix and OLS estimator of β , we can do test any hypothesis about . (5) DNA. We can use R 2 for model comparison only if the models to be compared use the same dependent variable. Q2: ˆ var( ) 1. Q3: (1) i) Use (B) to test for heteroskedasticity: Koenker’s test = T R 2 = 30 > 3.84 = c from χ 2 (1) at 95%. ii) Use GLS for random coefficient models (See the class notes for detailed estimation procedure). (2) Use (C): LM-type test = T R 2 = 5 > 3.84 = c from 2 (1). (3) Do the Prais-Winston GLS: Using (D), we can obtain ˆ = 0.4. Using this value, do the Prais-Winston transformation. Then, estimate the transformed equation by OLS.

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