Homework Answers
ANSWER
GIVEN THAT
While using Diebold Mariano statistic , null will be rejected when
Here,
|1.78 | < 1.65
Hence, we fail to reject the null ,
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Consider two models for the variable Yt: MA: Yt = Bo + B1 Yt-1 + Ut...
Consider the model, Yt = Bo + B1 Xt + Ut, and this is estimated using...
Consider the model, Yt = Bo + B1 Xt + Ut, and this is estimated using OLS with 65 observations. However, it is suspected autocorrelation is present. You compute the DW statistic as 1.64. The critical values for this model are: du = 1.407 and du = 1.467. What is your decision? O A. Reject the null O B. Fail to reject the null. O C. Undetermined or inconclusive.
Consider the model, Yt = BO+B1 X1,t + B1 X2,t + Ut, and this is estimated...
Consider the model, Yt = BO+B1 X1,t + B1 X2,t + Ut, and this is estimated using OLS with 250 observations. However, it is suspected autocorrelation is present. You compute the DW statistic as 1.997. The critical values for this model are: dL = 1.692 and du = 1.724. What is your decision? A. Reject the null. B. Fail to reject the null. C. Undetermined or inconclusive.
Consider the model defined by, Yt = BO + B1 Yt-1 + B2 Xt + Ut....
Consider the model defined by, Yt = BO + B1 Yt-1 + B2 Xt + Ut. Compute the long-run coefficients (2 decimals) for the model: Short-Run Long-Run BO 1.38 B1 0.60 B2 -5.26
Consider the model, Yt = B0 + B1 X1,t + B1 X2,t + Ut, and this...
Consider the model, Yt = B0 + B1 X1,t + B1 X2,t + Ut, and this is estimated using OLS with 350 observations. However, it is suspected autocorrelation is present. You compute the DW statistic as 0.891. The critical values for this model are: dL = 1.741 and dU = 1.764. What is your decision? A. Reject the null. B. Fail to reject the null. C. Undetermined or inconclusive.
Consider the model, Yt = BO+B1 Xt + Ut, and this is estimated using OLS with...
Consider the model, Yt = BO+B1 Xt + Ut, and this is estimated using OLS with 65 observations. However, it is suspected autocorrelation is present. You estimate the residuals (Uhatt) on the lag of residuals (Uhatt-1), Xt, and a constant. These estimation results are presented in the table below. Coefficient Std. Error Intercept Uhatt-1 Xt 0.006 0.052 0.004 0.051 0.002 0.001 0.004 R2 Adjusted-R2 0.003 Make your decision on autocorrelation and choose the most appropriate action from the responses. A....
Consider the model, Yt = BO+B1 Xt + Ut, and this is estimated using OLS with...
Consider the model, Yt = BO+B1 Xt + Ut, and this is estimated using OLS with 65 observations. However, it is suspected autocorrelation is present. You estimate the residuals (Uhatt) on the lag of residuals (Uhatt-1), Xt, and a constant. These estimation results are presented in the table below. Std. Error Coefficient 0.006 0.004 Intercept Uhatt-1 Xt 0.052 0.051 0.001 0.002 0.004 R2 Adjusted-R2 0.003 Make your decision on autocorrelation and choose the most appropriate action from the responses. O...
Consider the model, Yt = BO+B1 Xt + Ut, and this is estimated using OLS with...
Consider the model, Yt = BO+B1 Xt + Ut, and this is estimated using OLS with 65 observations. However, it is suspected autocorrelation is present. You estimate the residuals (Uhatt) on the lag of residuals (Uhatt-1), Xt, and a constant. These estimation results are presented in the table below. Coefficient Std. Error 0.824 Intercept Uhatt-1 Xt 10.412 0.198 0.325 0.052 0.064 Adjusted-R2 0.122 0.107 Make your decision on autocorrelation and choose the most appropriate action from the responses. A. Not...
Consider the model, Yt = Bo + B1 X1,1+B1 X2,t + Ut, and this is estimated...
Consider the model, Yt = Bo + B1 X1,1+B1 X2,t + Ut, and this is estimated using OLS with 350 observations. You run some tests with the following results: DWH fails to reject, BG fails to reject, and White test rejects. Select the combination of approaches for the most appropriate estimation of the coefficients. A. Use 2 SLS B. Heteroskedastic correction using X2,t only. c. Use Newey-West HAC. D. Use OLS. Heteroskedastic correction using X1,t only. F. Use White's heteroskedastic-consistent...
Consider the model, Yi = Bo + B1 X1,1 + B2 X2,1 + Uj, where sorting...
Consider the model, Yi = Bo + B1 X1,1 + B2 X2,1 + Uj, where sorting the residuals based on the X1, and X2,i gives: X1 X2 SSE-F 13.7 67.2 SSE-L 85.2 52.0 Compute the Goldfeld-Quandt statistic and decide if there is heteroskedasticity present for either regressor at the 5% critical-F value of 1.313 A. Not enough information. B. Reject the null for X1, and fail to reject for X2. C. Reject the null for X1, and reject the null...
Consider the model, Yi = Bo + B1 Xi + Uj, where you suspect Xi is...
Consider the model, Yi = Bo + B1 Xi + Uj, where you suspect Xi is endogenous. You have an exogenous instrument and you estimate the first stage to recover the residuals, Vhati. You want to test for endogeneity so you estimate the following model using OLS: Y; = Bo + B1 Xì + B2 Vhat; + Uj. The estimation results from 100 observations are in the table: Coefficient Standard Errors constant 2.96 0.47 X 0.75 0.85 Vhat 0.37 0.15...
Consider the model, Yt = Bo + B1 Xt + Ut, and this is estimated using OLS with 65 observations. However, it is suspected autocorrelation is present. You compute the DW statistic as 1.64. The critical values for this model are: du = 1.407 and du = 1.467. What is your decision? O A. Reject the null O B. Fail to reject the null. O C. Undetermined or inconclusive.
Consider the model, Yt = BO+B1 X1,t + B1 X2,t + Ut, and this is estimated using OLS with 250 observations. However, it is suspected autocorrelation is present. You compute the DW statistic as 1.997. The critical values for this model are: dL = 1.692 and du = 1.724. What is your decision? A. Reject the null. B. Fail to reject the null. C. Undetermined or inconclusive.
Consider the model defined by, Yt = BO + B1 Yt-1 + B2 Xt + Ut. Compute the long-run coefficients (2 decimals) for the model: Short-Run Long-Run BO 1.38 B1 0.60 B2 -5.26
Consider the model, Yt = BO+B1 Xt + Ut, and this is estimated using OLS with 65 observations. However, it is suspected autocorrelation is present. You estimate the residuals (Uhatt) on the lag of residuals (Uhatt-1), Xt, and a constant. These estimation results are presented in the table below. Coefficient Std. Error Intercept Uhatt-1 Xt 0.006 0.052 0.004 0.051 0.002 0.001 0.004 R2 Adjusted-R2 0.003 Make your decision on autocorrelation and choose the most appropriate action from the responses. A....
Consider the model, Yt = BO+B1 Xt + Ut, and this is estimated using OLS with 65 observations. However, it is suspected autocorrelation is present. You estimate the residuals (Uhatt) on the lag of residuals (Uhatt-1), Xt, and a constant. These estimation results are presented in the table below. Std. Error Coefficient 0.006 0.004 Intercept Uhatt-1 Xt 0.052 0.051 0.001 0.002 0.004 R2 Adjusted-R2 0.003 Make your decision on autocorrelation and choose the most appropriate action from the responses. O...
Consider the model, Yt = BO+B1 Xt + Ut, and this is estimated using OLS with 65 observations. However, it is suspected autocorrelation is present. You estimate the residuals (Uhatt) on the lag of residuals (Uhatt-1), Xt, and a constant. These estimation results are presented in the table below. Coefficient Std. Error 0.824 Intercept Uhatt-1 Xt 10.412 0.198 0.325 0.052 0.064 Adjusted-R2 0.122 0.107 Make your decision on autocorrelation and choose the most appropriate action from the responses. A. Not...
Consider the model, Yt = Bo + B1 X1,1+B1 X2,t + Ut, and this is estimated using OLS with 350 observations. You run some tests with the following results: DWH fails to reject, BG fails to reject, and White test rejects. Select the combination of approaches for the most appropriate estimation of the coefficients. A. Use 2 SLS B. Heteroskedastic correction using X2,t only. c. Use Newey-West HAC. D. Use OLS. Heteroskedastic correction using X1,t only. F. Use White's heteroskedastic-consistent...
Consider the model, Yi = Bo + B1 X1,1 + B2 X2,1 + Uj, where sorting the residuals based on the X1, and X2,i gives: X1 X2 SSE-F 13.7 67.2 SSE-L 85.2 52.0 Compute the Goldfeld-Quandt statistic and decide if there is heteroskedasticity present for either regressor at the 5% critical-F value of 1.313 A. Not enough information. B. Reject the null for X1, and fail to reject for X2. C. Reject the null for X1, and reject the null...
Consider the model, Yi = Bo + B1 Xi + Uj, where you suspect Xi is endogenous. You have an exogenous instrument and you estimate the first stage to recover the residuals, Vhati. You want to test for endogeneity so you estimate the following model using OLS: Y; = Bo + B1 Xì + B2 Vhat; + Uj. The estimation results from 100 observations are in the table: Coefficient Standard Errors constant 2.96 0.47 X 0.75 0.85 Vhat 0.37 0.15...
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