Before we move on to Structural Break Models, let's have an introduction about Structural Breaks itself. Structural Breaks are nothing but sudden change in the parameters of the time series as well as panel data.
Structural Breaks are influenced by economic policies.
"Structural change is pervasive in economic time series relationships, and it can be quite perilous to ignore. Inferences about economic relationships can go astray, forecasts can be inaccurate, and policy recommendations can be misleading or worse." -- Bruce Hansen (2001)There are Structural Break tests which helps you identify as well as quantity the breaks. Below is the list of some well known Break Point Tests
CUSUM's Test (Cumulative sum test for parameter stability)
Quandt-Andrews Breakpoint Test : one or more unknown structural breakpoints
Bai and Perron Tests: Extended the Quandt-Andrews framework by allowing for multiple unknown breakpoints (Dynamic Programming model)
Chow's Break Point Tests: Same equation is fitted for two subsamples to check the significant difference in estimated equations. The break date can also defined into the model.
So, What's next once you identify a structural break in your data?
Structural Adjustments is the answer. Soon it will discussed here.
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