Description:
The paper presents an approach to the analysis of data that contains (multiple) structural changes in a linear regression setup. We implement various strategies which have been suggested in the literature for testing against structural changes as well as a dynamic programming algorithm for the dating of the breakpoints in the R statistical software package. Using historical data on Nile river discharges, road casualties in Great Britain and oil prices in Germany it is shown that changes in the mean of a time series as well as in the coefficients of a linear regression are easily matched with identifiable historical, political or economic events.