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Assessing U.S. Aggregate Fluctuations Across Time and Frequencies

Christian Matthes (), Thomas Lubik () and Fabio Verona ()

No 19-6, Working Paper from Federal Reserve Bank of Richmond

Abstract: We study the behavior of key macroeconomic variables in the time and frequency domain. For this purpose, we decompose U.S. time series into various frequency components. This allows us to identify a set of stylized facts: GDP growth is largely a high-frequency phenomenon whereby inflation and nominal interest rates are characterized largely by low-frequency components. In contrast, unemployment is a medium-term phenomenon. We use these decompositions jointly in a structural VAR where we identify monetary policy shocks using a sign restriction approach. We find that monetary policy shocks affect these key variables in a broadly similar manner across all frequency bands. Finally, we assess the ability of standard DSGE models to replicate these findings. While the models generally capture low-frequency movements via stochastic trends and business-cycle fluctuations through various frictions, they fail at capturing the medium-term cycle.

Keywords: Wavelets; bandpass filter; SVAR; sign restrictions; DSGE model (search for similar items in EconPapers)
JEL-codes: C32 C51 E32 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-dge and nep-mac
Date: 2019-02-28
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https://www.richmondfed.org/-/media/richmondfedorg ... wp19-06_appendix.pdf Supplementary Appendix (application/pdf)

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