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A BVAR Model for Forecasting Ukrainian Inflation

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Abstract

In this paper, I examine the forecasting performance of a Bayesian Vector Autoregression (BVAR) model with steady-state prior and compare the accuracy of the forecasts against the forecasts of QPM model and official NBU forecasts over the period 2016q1–2020q1. My findings suggest that inflation forecasts produced by the BVAR model are more accurate than those of the QPM model two quarters ahead and are competitive for the longer horizon. For GDP growth, the forecasts of the BVAR outperform those of the QPM for the whole forecast horizon. For inflation they also outperform the official NBU forecasts over the monetary policy horizon, whereas the opposite is true for the forecasts of the GDP growth.

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  • Nadiia Shapovalenko, 2021. "A BVAR Model for Forecasting Ukrainian Inflation," IHEID Working Papers 05-2021, Economics Section, The Graduate Institute of International Studies.
    • Handle: RePEc:gii:giihei:heidwp05-2021
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    1. Fabian Krüger & Todd E. Clark & Francesco Ravazzolo, 2017. "Using Entropic Tilting to Combine BVAR Forecasts With External Nowcasts," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 470-485, July.
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    More about this item

    Keywords

    BVAR; forecast evaluation; inflation forecasting;
    All these keywords.

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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