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- QUESTION 8 Having many relevant instruments: a. is good because they provide more information. b. is a problem because instead of being just identified, the regression now becomes overidentified. С. typically results in larger standard errors for the TSLS estimator. d. is not as important for inference as having the same number of endogenous variables as instruments. е. All of the above. O f. None of the above.QUESTION 8 Having many relevant instruments: a. is good because they provide more information. D. is a problem because instead of being just identified, the regression now becomes overidentified. С. typically results in larger standard errors for the TSLS estimator. d. is not as important for inference as having the same number of endogenous variables as instruments. е. All of the above. O f. None of the above.Consider the regression model Yi=bot Bi Xitui Suppose that you know Bo = 0. Derive the formula for the least squares estimator of B₁. The least squares objective function is O A. n O B. O C. O D. E (Yi-bo-b1Xi) i=1 n Σ (Yi-bo-biXi) i=1 2 n Σ (v₁²-bo-b₁x₁²) i=1 n E (Yi-bo-b+Xi) 3 i=1
- 1. You are interested the causal effect of X on Y, B1. Suppose that X, and X2 are uncorrelated. You estimate B1 by regressing Y onto X1 (so that X2 is not included in the regression). Does this estimator suffer from omitted variable bias due to the exclusion of X2? (a) Yes (b) No (c) Maybe 2. Omitted variable bias violates which of the following assumptions: (a) The conditional distribution of u, given X1i X2i, ...Xki has a mean of zero (b) (Xi, X2i...Y;), i = 1, ., n are independently and identically distributed (c) Heteroskedasticity (d) Perfect multicollinearityq8- Which of the following statistics can be used to assess out-of-sample predictive ability of the model? Select one: a. Adjusted R2 b. Standard error of regression c. R2 d. Theil's U2.a) The R? should not be used to choose the best econometric model specification in multiple regression models. True or False
- 2. In a multiple regression of y on x1, x2, and x3, including additional variables on the right-hand side of the model always increases R2. (True/False).The OLS estimators of the coefficients in multiple regression will have omitted variable bias: a. i only if an omitted determinant of b. if an omitted variable is correlated with at least one of the regressors, even though it is not a determinant of the dependent variable. C. only if the omitted variable is not normally distributed. d. if an omitted determinant of is a continuous variable. Y; i is correlated with at least one of the regressors. e. if the degree of freedom is less than 50.Yi = B1 + B2xi2 + · · · + Brxik + ei, i = 1, . .., N, var (e; X) = var (y:|X) = o? Which property of linear regression model is most appropriate for the above regression? Select one: O a. heteroskedasticity O b. strict exogeneity c. autocorrelation O d. model mis-specification
- Discuss the FIVE (5) importance of adding error term in the regression model.4. From the regression output, report the coefficients, standard errors, t-statistics, probability and R-squared (report the results in a table). 5. Re-write the specified model in (a) with values from the regression results and interpret the coefficients.The following graph of the estimated residuals from a regression against the observation date (i.e. time period) indicates the residuals are: 2.00 1.50 1.00 0.50 00 0.00 -0.50 -1.00 1.50 -2.00 Time Select one: O A. Serially correlated O B. Normally distributed OC. Homoscedastic O D. Serially uncorrelated O E. Heteroscedastic Estimated residuals