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Iterated Multi-Step Forecasting with Model Coefficients Changing Across Iterations

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  • Michal Franta

Abstract

Iterated multi-step forecasts are usually constructed assuming the same model in each forecasting iteration. In this paper, the model coefficients are allowed to change across forecasting iterations according to the in-sample prediction performance at a particular forecasting horizon. The technique can thus be viewed as a combination of iterated and direct forecasting. The superior point and density forecasting performance of this approach is demonstrated on a standard medium-scale vector autoregression employing variables used in the Smets and Wouters (2007) model of the US economy. The estimation of the model and forecasting are carried out in a Bayesian way on data covering the period 1959Q1-2016Q1.

Suggested Citation

  • Michal Franta, 2016. "Iterated Multi-Step Forecasting with Model Coefficients Changing Across Iterations," Working Papers 2016/05, Czech National Bank.
  • Handle: RePEc:cnb:wpaper:2016/05
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    File URL: https://www.cnb.cz/export/sites/cnb/en/economic-research/.galleries/research_publications/cnb_wp/cnbwp_2016_05.pdf
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    References listed on IDEAS

    as
    1. Kapetanios, George & Price, Simon & Theodoridis, Konstantinos, 2015. "A new approach to multi-step forecasting using dynamic stochastic general equilibrium models," Economics Letters, Elsevier, vol. 136(C), pages 237-242.
    2. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2006. "A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 499-526.
    3. Jan Bruha & Jaromir Tonner, 2014. "The Czech Housing Market Through the Lens of a DSGE Model Containing Collateral-Constrained Households," Working Papers 2014/09, Czech National Bank.
    4. Schorfheide, Frank, 2005. "VAR forecasting under misspecification," Journal of Econometrics, Elsevier, vol. 128(1), pages 99-136, September.
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    More about this item

    Keywords

    Bayesian estimation; direct forecasting; iterated forecasting; multi-step forecasts; VAR;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • 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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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