TESTING FOR HOMOSCEDASTICITY & NORMALITY IN E –VIEWS
GENERATING RESIDUALS AND FITTED VALUES IN E-VIEWS
Generating Residuals:
All you have to do is run a regression in E-views and E-views automatically saves the
residuals from the latest regression in a variable called resid.
How do you see
residual values?
Step 1: One way
to see a table of
residual and fitted
values is to first
run the regression
by going to
Quick/Estimate
Equation and
typing in the
equation into the
box and clicking
o.k.
Step 2: After the equation results
pop up click on the “View” box
in the equation results window.
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Step 3: Scroll down to “Actual, Fitted, Residual” and select actual fitted residual table.
Step 4: The actual, fitted residual table will look like this:
Next if
you
like
you
can
copy
and
paste
the
residua
l and
fitted
column
s of
data
into
Excel
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and plot Residual Vs. Predicted values. Or… you can do the following to do the plot in
E-views.
PLOTTING RESID Vs. FITTED VALUES IN E-Views
Step1: Generate fitted values in E-views. Start with the estimation box and click on the
forecast button.
Next e-views will
generate a new
variable to store
the fitted values of
the dependent
variable. It
usually takes the
name of the
dependent
variable and adds
and F to it. SO
OUR FIITED
VARIABLE
WILL BE yf
Click on the OK
button and yf
will be created.
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You will see a graph like the one below. This is NOT WHAT YOU WANT.
Next go up to the “Quick”
menu at the main E-views
toolbar. Scroll down to
“Graph” and select “Scatter”
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Then type in Resid (type in a space) and yf and hit OK.
After you hit OK you get the desired graph of Resid Vs. Fitted values that you want!!
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GENERATING THE WHITE STAT FOR THE WHITE TEST
Step 1: From the regression equations results box click on “View”
Step 2: Scroll down to “Residual Tests” and click on “White Heteroskedasticity no cross
terms”
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The output that follows gives you White’s Test statistic. If this number is larger than the
critical Chi-square value from the table you have a problem with Heteroskedasticity.
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To Adjust the Standard Errors to account for Heteroscedasticity - from the
equation output window click on estimate and then click on OPTIONS.
Then check the box for Heteroscedasticty consistent coefficient covariance.
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Then click OK a couple of times and you should get regression results with standard
errors that are adjusted for Heteroscedasticity
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GENERATING THE JARQUE-BERA STAT
Step 1: From the regression equations results box click on “View”
Step 2: Scroll down to “Residual Tests” and click on “Histogram-Normality”
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Step 3: Read the Jarque Bera stat to the right of the Histogram, if the number is bigger
than 5.99 (Chi-square with 2 df at the 5 % level) your error terms are not normally
distributed and you have a problem.
If you have a problem with normality consider using a transformation of the
dependent variable such as Log(Y), 1/Y, Suare Root(Y) etc.
If that does not work – see your thesis advisor.