Measuring business cycles using vars

Patrick Fève and Alban Moura
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Patrick Fève: TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement

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Abstract: We propose to measure business cycles using vector autoregressions (VARs). Our method builds on two insights: VARs automatically decompose the data into stable and unstable components, and variance-based shock identfication can extract meaningful cycles from the stable part. This method has appealing properties: (1) it isolates a well-defined component associated with typical fluctuations; (2) it ensures stationarity by construction; (3) it targets movements at business-cycle frequencies; and (4) it is backward-looking, ensuring that cycles at each date only depend on current and past shocks. Since most existing filters lack one or more of these features, our method offers a valuable alternative. In an empirical application, we show that the two shocks with the largest cyclical impact effectively capture postwar U.S. business cycles and we find a tighter link between real activity and inflation than previously recognized. We compare our method with standard alternatives and document the plausibility and robustness of our results.

Keywords: Filtering; Shocks; Vector autoregressions; Detrending; Business cycles (search for similar items in EconPapers)
Date: 2025-10-14
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Working Paper: Measuring business cycles using VARs (2025)
Working Paper: Measuring business cycles using vars (2025)
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