n estimating the regression in problem #2 you are also 4. concemed that the tstatistics may be inflated because of the presence of conditional heteroscedasticity.

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The questions are correlated to the ones that I have added before it's a set of 4 qstns
n estimating the regression in problem #2 you are also
4.
concened 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:
0.414
Multiple R
0.171
81
0.160
R Square
Adjusted R Square
92 37
60
SEE
a.
Conduct a test at the level to see if conditional heteroskedasticity is present
b.
in view of your answer for a), what needs to be done?
Transcribed Image Text:n estimating the regression in problem #2 you are also 4. concened 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: 0.414 Multiple R 0.171 81 0.160 R Square Adjusted R Square 92 37 60 SEE a. Conduct a test at the level to see if conditional heteroskedasticity is present b. in view of your answer for a), what needs to be done?
A In estimating the regression in the previous problem (#2), you
are concemeu that the t-statistics may be inflated because of serial correlation.
You compute the DW statistic at 0.724 for the regression
Based on the DW, what can you say about serial correlation between the
residuals? Are they positively or negatively correlated? Or not correlated?
b.
Compute the sample correlation between the regression residuals from one
period and those from the previous period,
C.
Perform a statistical test at the level to see if there is serial correlation, If
you are using the table in the textbook, assume that the critical values of the
DW statistic for 214 observations are about 0.11 higher than the critical
values for 100 observations.
Transcribed Image Text:A In estimating the regression in the previous problem (#2), you are concemeu that the t-statistics may be inflated because of serial correlation. You compute the DW statistic at 0.724 for the regression Based on the DW, what can you say about serial correlation between the residuals? Are they positively or negatively correlated? Or not correlated? b. Compute the sample correlation between the regression residuals from one period and those from the previous period, C. Perform a statistical test at the level to see if there is serial correlation, If you are using the table in the textbook, assume that the critical values of the DW statistic for 214 observations are about 0.11 higher than the critical values for 100 observations.
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