Trend-cycle correlation, drift break and the estimation of trend and cycle in Canadian GDP
AbstractUnivariate correlated trend cycle models are highly sensitive to the specifications of breaks in the data. This paper argues, using Monte Carlo experiments, that a bivariate correlated unobserved components (UC) framework with breaks delivers substantially more accurate results for the trend-cycle parameters than the corresponding univariate frameworks in a finite sample size. The paper estimates stochastic trend and cyclical fluctuations in Canada from a bivariate UC model. Results show a fairly volatile stochastic trend after the drift break and the negative trend-cycle shock correlation are accounted for. The estimated cyclical component is large, persistent, and consistent with ECRI denoted Canadian recessions.
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Bibliographic InfoArticle provided by Canadian Economics Association in its journal Canadian Journal of Economics.
Volume (Year): 40 (2007)
Issue (Month): 2 (May)
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Postal: Canadian Economics Association Prof. Steven Ambler, Secretary-Treasurer c/o Olivier Lebert, CEA/CJE/CPP Office C.P. 35006, 1221 Fleury Est Montréal, Québec, Canada H2C 3K4
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Other versions of this item:
- Arabinda Basistha, 2005. "Trend-Cycle Correlation, Drift Break and the Estimation of Trend and Cycle in Canadian GDP," Working Papers 05-07 Classification- JEL, Department of Economics, West Virginia University.
- E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
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