In Stata, how do I conduct the Chow Test?
The Chow Test examines whether parameters (slopes and the intercept) of one group are different from those of other groups. If you are interested only in differences among intercepts, try a dummy variable regression model (fixed-effect model).
Suppose you suspect that the impact of
motivation varies across companies; the slope
salary of one company is different from the slopes of
other companies. For the sake of convenience, consider only two
d=1 or 0) here;
culture are covariates.
The pooled model, which assumes both companies have the same slopes and intercept, is as follows:. regress motivation salary size culture
You may fit separate regressions as follows:. regress motivation salary size culture if d==1 // for company 1 . regress motivation salary size culture if d==0 // for company 2
For the Chow Test, create an interaction term of the regressor
salary and the dummy variable
d, and then
fit the model with the interaction and the dummy as follows:
The coefficient of
d is the deviation of the second
company's intercept from the baseline intercept
d=0). Likewise, the coefficient of
is the slope of the baseline company, and the coefficient of
salary_d is the deviation of the comparison group's slope
from the baseline slope.
Now, conduct the Chow Test using the
command. The null hypothesis is that two companies have equal
salary and intercept; deviations of the
slope and intercept are not statistically discernible from zero.
notest option suppresses the output, and
accum tests a hypothesis jointly with a previously tested
one. Rejection of the null hypothesis means that two companies do not
share the same intercept and slope of
For more details about the Chow Test, see Stata's Chow tests FAQ.
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Last modified on July 30, 2013.