(b) The following OLS regression results and White Heteroscedasticity Test are obtained from Eviews for the following regression model C = B% +BiYdu + B,W + B-IR + E. 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 Coefficient Std. Error t-Statistic Prob. -20.71811 12.83272 -1.614476 0.1127 YD 0.013758 0.002484 0.733991 53.34991 0.0000 0.035985 14.48563 0.0000

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(b) The following OLS regression results and White Heteroscedasticity Test are obtained from
Eviews for the following regression model C, = B% +ß1Yd + B,Wi + B•IR + Ei.
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
Coefficient
Std. Error
t-Statistic
Prob.
C
-20.71811
12.83272
-1.614476
0.1127
YD
0.733991
0.013758
53.34991
0.0000
0.002484
2.307678
0.0000
0.0204
W
0.035985
14.48563
-2.394320
IR
-5.525320
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
Mean dependent var
S.D. dependent var
Akaike info criterion
0.999401
2888.296
0.999365
1500.920
37.81573
71501.48
-270.7119
10.17451
Schwarz criterion
10.32185
Hannan-Quinn criter.
10.23133
27814.08
Durbin-Watson stat
1.310017
0.000000
Heteroskedasticity Test: White
F-statistic
Obs*R-squared
Scaled explained SS
Prob. F(9,44)
Prob. Chi-Square(9)
Prob. Chi-Square(9)
0.0000
0.0001|
0.0000
7.573275
32.81588
53.99769
Does the problem of Heteroscedasticity exist in this regression model? Justify your answers.
Transcribed Image Text:(b) The following OLS regression results and White Heteroscedasticity Test are obtained from Eviews for the following regression model C, = B% +ß1Yd + B,Wi + B•IR + Ei. 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 Coefficient Std. Error t-Statistic Prob. C -20.71811 12.83272 -1.614476 0.1127 YD 0.733991 0.013758 53.34991 0.0000 0.002484 2.307678 0.0000 0.0204 W 0.035985 14.48563 -2.394320 IR -5.525320 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) Mean dependent var S.D. dependent var Akaike info criterion 0.999401 2888.296 0.999365 1500.920 37.81573 71501.48 -270.7119 10.17451 Schwarz criterion 10.32185 Hannan-Quinn criter. 10.23133 27814.08 Durbin-Watson stat 1.310017 0.000000 Heteroskedasticity Test: White F-statistic Obs*R-squared Scaled explained SS Prob. F(9,44) Prob. Chi-Square(9) Prob. Chi-Square(9) 0.0000 0.0001| 0.0000 7.573275 32.81588 53.99769 Does the problem of Heteroscedasticity exist in this regression model? Justify your answers.
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