The standard linear regression model described in “Basic Regression Analysis” assumes that the parameters of the model do not vary across observations.

Despite this assumption. structural change, the changing of parameters at dates in the sample period, plays an empirically relevant role in applied time series analysis. Accordingly, there has been a large volume of work targeted at developing testing and estimation methodologies for regression models which allow for change. Hansen (2001) and Perron (2006) offer useful overviews of the literature.

This chapter describes the EViews tools for estimating linear regression models that are subject to structural change. The regime breakpoints may be known and specified a priori, or they may be estimated using the Bai (1997), Bai and Perron (1998), and related techniques.

Note that much of the material in this chapter parallels the closely related subject of testing for multiple breakpoints outlined in “Multiple Breakpoint Tests”.