Measuring Business Cycles with Structural Breaks and Outliers: Applications to International Data

Pierre Perron and Tatsuma Wada

No wp2015-016, Boston University - Department of Economics - Working Papers Series from Boston University - Department of Economics

Abstract: This paper first generalizes the trend-cycle decomposition framework of Perron and Wada (2009) based on unobserved components models with innovations having a mixture of normals distribution, which is able to handle sudden level and slope changes to the trend function as well as outliers. We investigate how important are the differences in the implied trend and cycle compared to the popular decomposition based on the Hodrick and Prescott (HP) (1997) filter. Our results show important qualitative and quantitative differences in the implied cycles for both real GDP and consumption series for the G7 countries. Most of the differences can be ascribed to the fact that the HP filter does not handle well slope changes, level shifts and outliers, while our method does so. Then, we reassess how such different cycles affect some socalled “stylized facts†about the relative variability of consumption and output across countries.

Keywords: Trend-Cycle Decomposition; Unobserved Components Model; International Business Cycle; Non Gaussian Filter (search for similar items in EconPapers)
JEL-codes: C22 E32 (search for similar items in EconPapers)
Date: 2015-10-29
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-mac and nep-opm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Measuring business cycles with structural breaks and outliers: Applications to international data (2016)
Working Paper: Measuring Business Cycles with Structural Breaks and Outliers: Applications to International Data (2014)
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