Rolling approaches (also known as rolling regression, recursive regression or reverse recursive regression) are often used in time series analysis to assess the stability of the model parameters with respect to time.
A common assumption of time series analysis is that the model parameters are time-invariant. However, as the economic environment often changes, it may be reasonable to examine whether the model parameters are also constant over time. One technique to assess the constancy of the model parameters is to compute the parameter estimates over a rolling window with a fixed sample size through the entire sample. If the parameters are truly constant over the entire sample, then the rolling estimates over the rolling windows will not change much. If the parameters change at some point in the sample, then the rolling estimates will show how the estimates have changed over time.
