Homework Answers
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, 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, Y; = Bo + B1 Xi+Uj, where you suspect Xi is endogenous. You...
Consider the model, Y; = 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, Vhatj. You want to test for endogeneity so you estimate the following model using OLS: Y= Bo + B1 Xi + B2 Vhat; + Uj. The estimation results from 100 observations are in the table: Coefficient Standard Errors Constant 2.63 0.98 X 0.97 0.57 Vhat 0.47 0.10 Please select your...
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...
2. For the quadratic model, where Y = Bo + B1 X1 + B2 X1 2...
2. For the quadratic model, where Y = Bo + B1 X1 + B2 X1 2 + ε, set forth the formula used to calculate the elasticity of Y with respect to X1.
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...
7.22. In the regression model Y; = Bo + B1Xi + B2(3X} – 2) +Ei, i...
7.22. In the regression model Y; = Bo + B1Xi + B2(3X} – 2) +Ei, i = 1,2,3, with X1 = -1, X2 = 0, and X3 = 1, what happens to the least squares estimates of Bo and B1 when B2 = 0? Why?
Assume that the variable Y is actually determined by the following equation Y; = Bo + B1X1,i+ B2X2,i + Uj additionally...
Assume that the variable Y is actually determined by the following equation Y; = Bo + B1X1,i+ B2X2,i + Uj additionally assume that corr(X1, X2) = p. The usual assumptions for a linear model hold in this case. You are interested in estimating B1. To accomplish this you collect a sample of the variables Y and X1 and estimate the following model Y; = Yo + 91X1,i+ vi (3) Answer the following questions 6. If p= 0 and B2 >...
1. In order to test whether the multiple linear regression model y bo +b,x1 + b2X2 is better than the average model (lazy model), which of the following null hypotheses is correct: a. Ho' b1...
1. In order to test whether the multiple linear regression model y bo +b,x1 + b2X2 is better than the average model (lazy model), which of the following null hypotheses is correct: a. Ho' b1 = b2 = 0 Но: B1 B2-0 с. We have a dataset Company with three variables: Sales, employees and stores. To build a multiple linear regression model using Sales as dependent variable, number of stores and number of employees as independent variables, which of the...
Consider a multiple linear regression model Y; = Bo + B1Xi1 + B22:2 + 33213 +...
Consider a multiple linear regression model Y; = Bo + B1Xi1 + B22:2 + 33213 + Blog(x14) + Ej. We have the following statistics for the regression Call: 1m formula = y “ x1 + x2 + x3 + log(x4) Coefficients: Estimate Std. Error t value Pr(>1t|) (Intercept) 154.1928 194.9062 0.791 0.432938 x1 -4.2280 2.0301 -2.083 0.042873 * x2 -6.1353 2.1936 -2.797 0.007508 ** x3 0.4719 0.1285 3.672 0.000626 *** x4 26.7552 9.3374 2.865 0.006259 ** Signif. codes: O '***'...
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, 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, Y; = 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, Vhatj. You want to test for endogeneity so you estimate the following model using OLS: Y= Bo + B1 Xi + B2 Vhat; + Uj. The estimation results from 100 observations are in the table: Coefficient Standard Errors Constant 2.63 0.98 X 0.97 0.57 Vhat 0.47 0.10 Please select your...
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...
2. For the quadratic model, where Y = Bo + B1 X1 + B2 X1 2 + ε, set forth the formula used to calculate the elasticity of Y with respect to X1.
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...
7.22. In the regression model Y; = Bo + B1Xi + B2(3X} – 2) +Ei, i = 1,2,3, with X1 = -1, X2 = 0, and X3 = 1, what happens to the least squares estimates of Bo and B1 when B2 = 0? Why?
Assume that the variable Y is actually determined by the following equation Y; = Bo + B1X1,i+ B2X2,i + Uj additionally assume that corr(X1, X2) = p. The usual assumptions for a linear model hold in this case. You are interested in estimating B1. To accomplish this you collect a sample of the variables Y and X1 and estimate the following model Y; = Yo + 91X1,i+ vi (3) Answer the following questions 6. If p= 0 and B2 >...
1. In order to test whether the multiple linear regression model y bo +b,x1 + b2X2 is better than the average model (lazy model), which of the following null hypotheses is correct: a. Ho' b1 = b2 = 0 Но: B1 B2-0 с. We have a dataset Company with three variables: Sales, employees and stores. To build a multiple linear regression model using Sales as dependent variable, number of stores and number of employees as independent variables, which of the...
Consider a multiple linear regression model Y; = Bo + B1Xi1 + B22:2 + 33213 + Blog(x14) + Ej. We have the following statistics for the regression Call: 1m formula = y “ x1 + x2 + x3 + log(x4) Coefficients: Estimate Std. Error t value Pr(>1t|) (Intercept) 154.1928 194.9062 0.791 0.432938 x1 -4.2280 2.0301 -2.083 0.042873 * x2 -6.1353 2.1936 -2.797 0.007508 ** x3 0.4719 0.1285 3.672 0.000626 *** x4 26.7552 9.3374 2.865 0.006259 ** Signif. codes: O '***'...
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10. Complete the table below
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AL CODE
EBX
EAX
[EAX]
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