The Chow test tells us whether the
regression coefficients are different for split data sets.
Basically, it tests whether one regression line or two separate
regression lines best fit a split set of data.
There are two assumptions of Chow
1. Error variance is the same for
the 2 periods
2. There exists a structural change
in the data.
The question says that there do not
exist a structural change in the data and you have to test whether
the error variance is the same for 2 periods.