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) 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
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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  1. ) 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

 

  1. 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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