One-Period Joint Forecasts of Polish Inflation, Unemployment and Interest Rate Using Bayesian VEC-MSF Models

Abstract

The paper aims at comparing forecast ability of VAR/VEC models with
a non-changing covariance matrix and two classes of Bayesian Vector Error
Correction – Stochastic Volatility (VEC-SV) models, which combine the VEC
representation of a VAR structure with stochastic volatility, represented by the
Multiplicative Stochastic Factor (MSF) process, the SBEKK form or the MSFSBEKK specification.
Based on macro-data coming from the Polish economy (time series of
unemployment, inflation and interest rates) we evaluate predictive density
functions employing of such measures as log predictive density score, continuous
rank probability score, energy score, probability integral transform. Each
of them takes account of different feature of the obtained predictive density
functions.