Iterated Multi-Step Forecasting with Model Coefficients Changing Across Iterations

Michal Franta

Working Papers from Czech National Bank, Research and Statistics Department

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.

Keywords: Bayesian estimation; direct forecasting; iterated forecasting; multi-step forecasts; VAR (search for similar items in EconPapers)
JEL-codes: C11 C32 C53 (search for similar items in EconPapers)
Date: 2016-06
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-for
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Persistent link: https://EconPapers.repec.org/RePEc:cnb:wpaper:2016/05

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