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Multivariate Structural Time Series Models - (Now published in 'System Dynamics in Economic and Financial Models', CHeij, H Schumacher, B Hanzon and C Praagman (eds.) John Wiley & Sons, Chichester (1997), pp.269-298.)

Author

Listed:
  • Andrew C Harvey
  • Siem Jan Koopman

Abstract

Much of economic analysis presupposes that certain economic time series can be decomposed into trends and cycles. Structural time series models are explicitly set up in terms of such unobserved components. This paper sets up various multivariate structural time series models, shows how they can model the data parsimoniously and how they can aid the analysis of the interrelationships between time series. he computations are carried out using the new STAMP 5.0 package. The graphics and diagnostics play a key role in the development of a model selection methodology.

Suggested Citation

  • Andrew C Harvey & Siem Jan Koopman, 1996. "Multivariate Structural Time Series Models - (Now published in 'System Dynamics in Economic and Financial Models', CHeij, H Schumacher, B Hanzon and C Praagman (eds.) John Wiley & Sons, Chichester (19," STICERD - Econometrics Paper Series 307, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    • Handle: RePEc:cep:stiecm:307
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    Cited by:

    1. Guilhem Bentoglio & Jacky Fayolle & Matthieu Lemoine, 2002. "Unity and Plurality of the European Cycle," Working Papers hal-03458584, HAL.
    2. Matteo Pelagatti & Valeria Negri, 2008. "Milan’s Cycle as an Accurate Leading Indicator for the Italian Business Cycle," Working Papers 20080601, Università degli Studi di Milano-Bicocca, Dipartimento di Statistica.

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