Change points and structural breaks

When performing an analysis that involves time series variables, we would usually want to make use of a sample period that has a consistent data generating process, when using a traditional linear regression model. To ensure that our selected sample period satisfies this criterion we could make use of a change point or structural break test to identify a change in the underlying data generating process. Since events such as the Global Financial Crisis and the Covid-19 pandemic, there is a growing need to be able to identify the location of multiple change points within time series. The literature on this area of work is extensive and recent advances consider the use of several different models at a level of generality that allow a host of interesting practical applications. These include models with stationary regressors and errors that can exhibit temporal dependence and heteroskedasticity, models with trending variables and possible unit roots and cointegrated models, among others. T

When performing an analysis that involves time series variables, we would usually want to make use of a sample period that has a consistent data generating process, when using a traditional linear regression model. To ensure that our selected sample period satisfies this criterion we could make use of a change point or structural break test to identify a change in the underlying data generating process. Since events such as the Global Financial Crisis and the Covid-19 pandemic, there is a growing need to be able to identify the location of multiple change points within time series. The literat