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Flexible trend-cycle decomposition of nonstationary multivariate time series

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  • Kosei Fukuda

Abstract

A flexible method for the trend-cycle decomposition of nonstationary multivariate time series is proposed. In this method, each time series is decomposed into a common or individual stochastic trend, a common or individual stationary cycle, and observation noise components. The combination of variables for a common trend or for a common cycle and the introduction of economic-theory-based trend are flexible and determined using the Akaike information criterion. Simulation results suggest that the proposed method works well, and two examples are shown to illustrate the efficacy of the proposed method, particularly by investigating the predictive accuracy.

Suggested Citation

  • Kosei Fukuda, 2007. "Flexible trend-cycle decomposition of nonstationary multivariate time series," Applied Economics, Taylor & Francis Journals, vol. 40(2), pages 135-147.
    • Handle: RePEc:taf:applec:v:40:y:2007:i:2:p:135-147
    DOI: 10.1080/00036840600749573
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