Filtering Persistent and Asymmetric Cycles

Abstract This paper evaluates the ability of the trend-cycle decomposition approach of Hamilton (2018. “Why You Should Never Use the Hodrick-Prescott Filter.” The Review of Economics and Statistics 100 (5): 831–43) to adequately characterize linear and (a)symmetric nonlinear business cycles fluctuations that are known to be persistent. This ability is contrasted to that of the Hodrick–Prescott filter. By means of Monte Carlo simulations, the results indicate that neither filter is able to preserve the cyclical properties of the data-generating process nor reproduce U.S. business cycles features, although this inability is exacerbated for the decomposition of Hamilton (2018. “Why You Should Never Use the Hodrick–Prescott Filter.” The Review of Economics and Statistics 100 (5): 831–43). Based on these findings, caution is called into question when this approach is applied to linear or nonlinear processes that are thought to exhibit persistence.