A unified approach to detecting unit root and structural break

Abstract

In the proposed approach, eight alternative data-generating processes (DGPs) are considered by combining a process with or without a unit root, a process with or without a trend break and a process with or without an innovation-variance break. It is determined on the basis of the selected model using the Bayesian information criterion which DGP generates the observed time series. The efficacy of the proposed approach is verified using comprehensive simulations, including comparisons with two conventional hypothesis-testing methods. The results of applying the proposed method to output time series for 20 developed countries suggest that 12 series have a trend break and 16 series have an innovation-variance break.