4. The OLS estimators for 1 and 2 are formulas derived by minimizing _____________. a.) the sum of the error terms or residualsb.) the sum of the squared residualsc.) the slope of the regression lined.) the fit of the regression line to the observed data.Ans: bLevel: EasySection: 2.35. Applying the OLS model to our data give us the following regression equation:ŷ = 3.41 + 12.89 x.What would the forecast value be when the independent variable is 15.0?6. In the OLS model, what happens to var(b1) as the sample size (N) increases?7. If b1 is an estimator for 1 such that E(b1) = 1 , then it must be the case that
8. Under the Gauss-Markov Theorem when assumptions SR1 – SR5 are met, what estimators of 1 and 2 may have smaller variances than b1 and b2?a.) noneb.) a non-linear estimatorc.) a normally distributed estimatord.) an estimator derived from economic theoryAns: bLevel: DifficultSection: 2.5
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- Winter '07