Bai and Perron's and spectral density methods for structural change detection in the US inflation process

Abstract

This paper addresses the issue of estimating the number of breaks and their locations in the monthly US inflation series using two different approaches to testing for structural changes. The first approach considers Bai and Perron's selection procedure based on a sequence of tests. This approach focuses on the instability problem in time. The second method uses a test similar to the one based on Kolmogorov–Smirnov statistics applied to the evolutionary spectrum. The results obtained are similar and economically significant.