Consider the following linear regression model: (a) Briefly describe the four steps in the White general...

 

Transcribed Image Text:

Consider the following linear regression model: (a) Briefly describe the four steps in the White general heteroscedasticity test. (b) The following OLS regression results and White Heteroscedasticity Test are obtained from Eviews for the following regression model C₁ = Bo + B₁Yd₁ + B₂W₂1 + B3IR31 + €1. where C= real consumption expenditure Yd = real disposable personal income W = real wealth IR = real interest rate Dependent Variable: CONS Method: Least Squares Sample: 1947 2000 Included observations: 54 Variable с Y₁ = Bo + B₁X₁1 + B₂X21 + B3X31 + E1 YD W IR R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) F-statistic Obs*R-squared t-Statistic Coefficient Std. Error -20.71811 12.83272 -1.614476 0.733991 0.013758 53.34991 0.035985 0.002484 14.48563 -5.525320 2.307678 -2.394320 0.999401 0.999365 37.81573 71501.48 -270.7119 27814.08 0.000000 Heteroskedasticity Test: White Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter.. Durbin-Watson stat Prob. 0.1127 0.0000 0.0000 0.0204 2888.296 1500.920 10.17451 10.32185 10.23133 1.310017 7.573275 Prob. F(9,44) 32.81588 Prob. Chi-Square(9) Scaled explained SS 53.99769 Prob. Chi-Square(9) Does the problem of Heteroscedasticity exist in this regression model? Justify your answers. 0.0000 0.0001 0.0000 Consider the following linear regression model: (a) Briefly describe the four steps in the White general heteroscedasticity test. (b) The following OLS regression results and White Heteroscedasticity Test are obtained from Eviews for the following regression model C₁ = Bo + B₁Yd₁ + B₂W₂1 + B3IR31 + €1. where C= real consumption expenditure Yd = real disposable personal income W = real wealth IR = real interest rate Dependent Variable: CONS Method: Least Squares Sample: 1947 2000 Included observations: 54 Variable с Y₁ = Bo + B₁X₁1 + B₂X21 + B3X31 + E1 YD W IR R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) F-statistic Obs*R-squared t-Statistic Coefficient Std. Error -20.71811 12.83272 -1.614476 0.733991 0.013758 53.34991 0.035985 0.002484 14.48563 -5.525320 2.307678 -2.394320 0.999401 0.999365 37.81573 71501.48 -270.7119 27814.08 0.000000 Heteroskedasticity Test: White Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter.. Durbin-Watson stat Prob. 0.1127 0.0000 0.0000 0.0204 2888.296 1500.920 10.17451 10.32185 10.23133 1.310017 7.573275 Prob. F(9,44) 32.81588 Prob. Chi-Square(9) Scaled explained SS 53.99769 Prob. Chi-Square(9) Does the problem of Heteroscedasticity exist in this regression model? Justify your answers. 0.0000 0.0001 0.0000

Answer rating: 100% (QA)

a The four steps in the white general heteroscedasticity test i Estimate the model using ... View the full answer