) In estimating the regression in problem #2, you are also concerned that the t-statistics may be inflated because of the presence of conditional heteroscedasticity. You conduct a regression of the squared residuals against the dummy variables X1, X2, and X3 and find that for the squared residuals regression: Multiple R 0.4145 R Square 0.1718 Adjusted R Square 0.1600 SEE 92.3760 Conduct a test at the level to see if conditional heteroskedasticity is present and from your results, what needs to be done?
) In estimating the regression in problem #2, you are also concerned that the t-statistics may be inflated because of the presence of conditional heteroscedasticity. You conduct a regression of the squared residuals against the dummy variables X1, X2, and X3 and find that for the squared residuals regression: Multiple R 0.4145 R Square 0.1718 Adjusted R Square 0.1600 SEE 92.3760 Conduct a test at the level to see if conditional heteroskedasticity is present and from your results, what needs to be done?
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Question
- ) In estimating the regression in problem #2, you are also concerned that the t-statistics may be inflated because of the presence of conditional heteroscedasticity.
You conduct a regression of the squared residuals against the dummy variables X1, X2, and X3 and find that for the squared residuals regression:
|
|
Multiple R |
0.4145 |
|
|
R Square |
0.1718 |
|
|
Adjusted R Square |
0.1600 |
|
|
SEE |
92.3760 |
- Conduct a test at the level to see if conditional heteroskedasticity is present and from your results, what needs to be done?
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