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.
Original language | English (US) |
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Pages (from-to) | 473-495 |
Number of pages | 23 |
Journal | B.E. Journal of Macroeconomics |
Volume | 23 |
Issue number | 1 |
DOIs | |
State | Published - Jan 1 2023 |
Bibliographical note
Publisher Copyright:© 2022 Walter de Gruyter GmbH, Berlin/Boston.
Keywords
- Markov-switching
- asymmetry
- business cycles
- detrending
- persistence