Suppose that you are performing the Regression test for AR(1)and you get (standard errors in parentheses)with 50 observations
$re\widehat {sidu}als _ { t } = 4.57 \text { residuals } _ { t - 1 }$
$\quad\quad\quad\quad\quad\quad(1.08)$
You would conclude that
A)autocorrelation is not present in the data.
B)autocorrelation is present in the data.
C)heteroskedasticity is not present in the data.
D)heteroskedasticity is present in the data.

Question

Suppose that you are performing the Regression test for AR(1)and you get (standard errors in parentheses)with 50 observations
 $re\widehat {sidu}als  _ { t } = 4.57 \text { residuals } _ { t - 1 }$
$\quad\quad\quad\quad\quad\quad(1.08)$
You would conclude that
A)autocorrelation is not present in the data.
B)autocorrelation is present in the data.
C)heteroskedasticity is not present in the data.
D)heteroskedasticity is present in the data.

Quizplus · Accepted Answer

The presence of a significant coefficient on lagged residuals suggests that autocorrelation is present in the data. The standard error of the coefficient is provided in parentheses and is not relevant for determining the presence of autocorrelation. Heteroskedasticity is not relevant for this particular test.

Suppose That You Are Performing the Regression Test for AR(1)and residu^alst=4.57 residuals t−1re\widehat {sidu}als _ { t } = 4.57 \text { residuals } _ { t - 1 }residualst​=4.57 residuals t−1​

Suppose That You Are Performing the Regression Test for AR(1)and $re\widehat {sidu}als _ { t } = 4.57 \text { residuals } _ { t - 1 }$