hechen UON TWO MULTIPLE CHONCOUSSINSON with consumption - SSC de vous of 5 to the equation Consumption.com www 11 A 5975 B 550 C 525 D. $300 5. The Gauss-Mark theorem w NOT hodit the error term has an expected value of a given any value of the intendere webles C, the regression model relies on the method of time angling for collecours D. the error term w is correlated with the regressors 6. Running regressions where each explanatory variable is estimated as a function of explanatory variables can help detect A. omitted relevant variables. B. inclevant variables included C. multicollinearity. D. heteroskedasiticity, 7. What are the consequences of using OLS when heteroskedasticity is present A. The OLS estimators are still BLUE B. Confidence intervals and hypothesis testing are invalid C. All coefficient estimators are based. D. It requires very large sample sizes to get efficient estimators 8. If your OLS estimated output includes an F-statistic and p-value for the overall significance of the regression model, how should you interpret the p-value? A. The probability that all of the coefficients are actually equal to zero B. The probability that all of the coefficients other than the intercept are actually zero and we would observe the estimated results. C. The probability that the model is completely invalid. D. The probability that the model is incorrectly specified, 9. Inclusion of an irrelevant variable as a regressor is not so harmful because A. the BLUE property of OLS estimators is not affected. B. the OLS estimators remain unbiased. C. the OLS estimators are still efficient. D. the OLS estimators are uniform. 1 ra y) E 10. To assess the effects of some explanatory variables on a dependent variable, you estimate 4 different models by adding an explanatory variable each time and get the following results: R? AIC Model A 0.3458 0.3285 22:56 Model B 0.3689 0.3394 22.37 Model C 0.4256 0.3916 21.21 Model D 0.4299 0.3911 21.79 Which model appears to be the best fitting model? . . C C D D 11. When using the weighted least squares to correct for heteroskedasticity, what weight should be used? A. Whatever weight scales of variables that creates a homoskedastic error variance. B. The inverse of the error variance at x. C. Whatever weight is determined by the Breush-Pagan test. D. The residuals from the initial regression model. -END