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An Alternative Trend-Cycle Decomposition using a State Space Model with Mixtures of Normals: Specifications and Applications to International Data Author info | Abstract | Publisher info | Download info | Related research | Statistics Tatsuma Wada () (Department of Economics, Boston University)
Pierre Perron () (Department of Economics, Boston University)
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This paper first generalizes the trend-cycle decomposition framework of Perron and Wada (2005) based on an unobserved components models with innovations having a mixtures 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. Third, we assess how such different cycles affect some socalled “stylized facts” about the relative variability of consumption and output across countries. Our results show again important differences. In particular, the crosscountry consumption correlations are generally higher than the output correlations, except for the period from 1975 to 1985, provided Canada is excluded. Our results therefore provide a partial solution to this puzzle. The evidence is particularly strong for the most recent period.
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Paper provided by Boston University - Department of Economics in its series Boston University - Department of Economics - Working Papers Series with number
WP2005-44.
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Length: 41 pages
Date of creation: Oct 2005Date of revision:
Handle: RePEc:bos:wpaper:wp2005-44Contact details of provider: Postal: 270 Bay State Road, Boston, MA 02215 Phone: 617-353-4389 Fax: 617-353-444 Web page: http://www.bu.edu/econ/ More information through EDIRC
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Keywords: Trend-Cycle Decomposition ; Unobserved Components Model ; International Business Cycle ; Non Gaussian Filter. ; Other versions of this item:
Find related papers by JEL classification: C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
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