A BVAR model for forecasting Ukrainian inflation - Nadiia Shapovalenko (Graduate Institute of International and Development Studies, 2021)
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.
Keywords: C30; C53; E37; 330; BVAR; forecast evaluation; inflation forecasting