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Forecasting macroeconomic variables using a structural state space model

Author

Listed:
  • de Silva, Ashton
Abstract
This paper has a twofold purpose; the first is to present a small macroeconomic model in state space form, the second is to demonstrate that it produces accurate forecasts. The first of these objectives is achieved by fitting two forms of a structural state space macroeconomic model to Australian data. Both forms model short and long run relationships. Forecasts from these models are subsequently compared to a structural vector autoregressive specification. This comparison fulfills the second objective demonstrating that the state space formulation produces more accurate forecasts for a selection of macroeconomic variables.

Suggested Citation

  • de Silva, Ashton, 2008. "Forecasting macroeconomic variables using a structural state space model," MPRA Paper 11060, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:11060
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    File URL: https://mpra.ub.uni-muenchen.de/11060/1/MPRA_paper_11060.pdf
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    References listed on IDEAS

    as
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    8. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    9. Renée Fry & James Hocking & Vance L. Martin, 2008. "The Role of Portfolio Shocks in a Structural Vector Autoregressive Model of the Australian Economy," The Economic Record, The Economic Society of Australia, vol. 84(264), pages 17-33, March.
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    12. Hyndman, Rob J. & Koehler, Anne B., 2006. "Another look at measures of forecast accuracy," International Journal of Forecasting, Elsevier, vol. 22(4), pages 679-688.
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    Cited by:

    1. Katsuyuki Shibayama, 2015. "Trend Dominance in Macroeconomic Fluctuations," Studies in Economics 1518, School of Economics, University of Kent.

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    More about this item

    Keywords

    State space; multivariate time series; macroeconomic model; forecast; SVAR;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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