Dummy variables for Chow Test?

Question

Why do we use them? What advantage does this have over not using them..? I don't get it. Thanks.

Answer 1

The final stage of the Chow Test is to compare the test statistic with the critical value from the F-Tables. The null hypothesis in this case is structural stability, if we reject the null hypothesis, it means we have a structural break in the data We then need to decide how to overcome this break.

If there is evidence of a structural break, it may mean we need to split the data into 2 samples and run separate regressions.

Another method to overcome this problem is to use dummy variables.The benefit of this approach is that we do not lose any degrees of freedom through a loss of observations.

Dummy Variables are a common way of solving structural breaks, as it does not involve splitting the data.

These variables consist of 1s and 0s and are often termed ‘on-off’ variables.

They can be used to determine the importance of policy actions on models and are often used to account for qualitative effects.

Their coefficients and t-statistics can then be interpreted in the usual way.

I hope this helps