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Consider the model, Yt = Bo + B1 X1,1+B1 X2,t + Ut, and this is estimated...
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, 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 X2,1 gives: X1 X2 Goldfeld-Quandt Statistic 1.475 0.843 If there is heteroskedasticity present at the 5% critical-F value of 1.624, then choose the most appropriate heteroskedasticity correction method. O A. Not enough information. OB. White's heteroskedastic-consistent standard errors C. Heteroskedastic correction based on X1. Ο Ο Ο D. Heteroskedastic correction based on X2. E. No heteroskedastic correction...
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 = 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...
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 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 two models for the variable Yt: MA: Yt = Bo + B1 Yt-1 + Ut...
Consider two models for the variable Yt: MA: Yt = Bo + B1 Yt-1 + Ut MB: Yt = A + A1 Yt-1 + A2 Xt + Vt While examining the prediction errors you obtain a Diebold-Mariano statistic of 1.78, what is your decision at the 10% significance level? A. Reject the null B. Fail to reject the null O C. Not enough information
Consider the model, Yt = 0.8 + 0.1 Yt-1 +0.5 X1,t + 1.7 X2,t + Ut....
Consider the model, Yt = 0.8 + 0.1 Yt-1 +0.5 X1,t + 1.7 X2,t + Ut. Complete the following table for the predicted values (2 decimals): 2018 2019 2020 2021 Year Yt 7.1 7.63 1.25 1.35 X1,5 KX2,0 1.30 1.9 1.40 2.4 2.5 3.20
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, Yi = Bo + B1 X1,1 + B2 X2,1 + Uj, where sorting the residuals based on the X1,; and X2,1 gives: X1 X2 Goldfeld-Quandt Statistic 1.475 0.843 If there is heteroskedasticity present at the 5% critical-F value of 1.624, then choose the most appropriate heteroskedasticity correction method. O A. Not enough information. OB. White's heteroskedastic-consistent standard errors C. Heteroskedastic correction based on X1. Ο Ο Ο D. Heteroskedastic correction based on X2. E. No heteroskedastic correction...
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 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 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 two models for the variable Yt: MA: Yt = Bo + B1 Yt-1 + Ut MB: Yt = A + A1 Yt-1 + A2 Xt + Vt While examining the prediction errors you obtain a Diebold-Mariano statistic of 1.78, what is your decision at the 10% significance level? A. Reject the null B. Fail to reject the null O C. Not enough information
Consider the model, Yt = 0.8 + 0.1 Yt-1 +0.5 X1,t + 1.7 X2,t + Ut. Complete the following table for the predicted values (2 decimals): 2018 2019 2020 2021 Year Yt 7.1 7.63 1.25 1.35 X1,5 KX2,0 1.30 1.9 1.40 2.4 2.5 3.20
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