Filtering Persistent and Asymmetric Cycles

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.