Cusum test eviews series#

Time series models are used for a variety of reasons - predicting future outcomes, understanding past outcomes, making policy suggestions, and much more. Inferences about economic relationships can go astray, forecasts can be inaccurate, and policy recommendations can be misleading or worse.' - Bruce Hansen (2001) 'Structural change is pervasive in economic time series relationships, and it can be quite perilous to ignore. $$ Why should I worry about structural breaks? The dependent variable $y_t$ is to be modeled as a linear combination of regressors with both time invariant coefficients, $x_t$, and time variant coefficients, $z_t$.ДЄlternatively, the variance break model assumes that breaks occur in the variance of the error term such that Bai and Perron (1998) provide the standard framework for structural breaks model in which some, but not all, of the model parameters are allowed to break at m possible break points, Structural break models can integrate structural change through any of the model parameters. Structural break models capture exactly these cases by incorporating sudden, permanent changes in the parameters of models. However, there are cases where changes in factors outside of the model cause changes in the underlying relationship between the variables in the model.