A short note on the application of Chow test of structural break in US GDP
The knowledge of structural break in U.S. GDP is important for a number of reasons: Firstly, a structural break may affect any or all of the underlying model parameters in U.S. GDP, which have different implications. For example, different researchers using the U.S. GDP data can easily reach quite opposite conclusions -- hardly an example of sound scientific practice. Secondly, despite the fact that US GDP is the most widely studied macroeconomic variable, yet, as popular news media regularly report, it is constantly and closely monitored by investors, academics as well as government officials all around the world. Thirdly, not only leading econometrics text books have used, in many cases, US GDP to illustrate examples of various time series data analysis, many highly influential economics journal articles, such as Nelson and Plosser (1982), Engel and Granger (1987), Perron (1989), Zivot and Andrews (1992), to name a few, have used GDP in their analysis. Last but not least, the National Bureau of Economic Research (NBER) uses GDP to declare whether and/or when the US economy enters and exits recession. Thus, shedding light on the previously unexplored characteristics of US GDP is justified.