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 MSF-SBEKK 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.

JO - Central European Journal of Economic Modelling and Econometrics L1 - http://journals.pan.pl/Content/112901/PDF/mainFile.pdf L2 - http://journals.pan.pl/Content/112901 PY - 2019 IS - No 1 EP - 45 KW - cointegration KW - stochastic volatility KW - Bayesian analysis KW - forecast verification A1 - Wróblewska, Justyna A1 - Pajor, Anna PB - Oddział PAN w Łodzi JF - Central European Journal of Economic Modelling and Econometrics SP - 23 T1 - One-Period Joint Forecasts of Polish Inflation, Unemployment and Interest Rate Using Bayesian VEC-MSF Models DA - 31.03.2019 UR - http://journals.pan.pl/dlibra/docmetadata?id=112901 DOI - 10.24425/cejeme.2019.129361 ER -