How can I do a Chow test with the robust variance estimates, that is, after estimating
with regress, vce(robust)?
| Title |
|
Chow and Wald tests |
| Author |
William Gould, StataCorp |
| Date |
July 1999; minor revision August 2007 |
First, see the FAQ How can I compute
a Chow test statistic?. The point of that FAQ is that you can do Chow
tests using Stata’s
test command
and, in fact, Chow tests are what the test command
reports.
Well, that’s not exactly right. test uses
the estimated variance–covariance matrix of the estimators, and
test performs Wald tests,
W = (Rb-r)'(RVR')-1 (Rb-r)
where V is the estimated
variance–covariance matrix of the estimators.
For linear regression with the conventionally estimated
V, the Wald test is the Chow test and vice
versa.
You might say that you are performing a Chow test, but I say that you are
performing a Wald test. That distinction is important, because the Wald
test generalizes to different variance estimates of
V, whereas the Chow test does not. After
regress,
vce(robust), for instance, test uses the
V matrix estimated by the robust method
because that is what regress, vce(robust) left
behind.
Thus the short answer is that you estimate your model using
regress, vce(robust) and then use Stata’s
test command. You then call the result a Wald
test.
If you are bothered that a Wald test produces F
rather than chi-squared statistics, also see the FAQ
Why does
test sometimes produce chi-squared and other times
F statistics?
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