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The Accuracy Of Macroeconomic Forecasts Based On Bayesian Vectorial-Autoregressive Models. Comparative Analysis Romania-Poland

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  • Mihaela SIMIONESCU

    (Institute for Economic Forecasting of the Romanian Academy, Bucharest, Romania)

  • Yuriy BILAN

    (Szczecin University, Faculty of Economics and Management, Szczecin, Poland)

Abstract

The aim of this research is to make predictions for macroeconomic variables like inflation rate, unemployment rate and exchange rate for Romania and Poland using BVAR models. The one-step-ahead forecasts cover the horizon 2011-2013. Direct forecasts were developed using three types of priors for data covering the period from 1990 to 2012: Minnesota priors, non-informative priors and natural-conjugate priors. The forecasts’ accuracy assessment based on generalized forecast error of second moment put in evidence the superiority of Poland’s predictions based on a BVAR(2) model, compared to Romania’s ones based on a BVAR(4) model for differenced and stationary data series. For inflation rate the forecasts are rather inaccurate, but for Poland the Minnesota priors and for Romania the non-informative priors determined the most accurate predictions for unemployment rate and exchange rate on the horizon 2011-2012. It is very likely that these types of priors generate the best forecasts in 2013

Suggested Citation

  • Mihaela SIMIONESCU & Yuriy BILAN, 2013. "The Accuracy Of Macroeconomic Forecasts Based On Bayesian Vectorial-Autoregressive Models. Comparative Analysis Romania-Poland," THE YEARBOOK OF THE "GH. ZANE" INSTITUTE OF ECONOMIC RESEARCHES, Gheorghe Zane Institute for Economic and Social Research ( from THE ROMANIAN ACADEMY, JASSY BRANCH), vol. 22(1), pages 5-10.
    • Handle: RePEc:zan:ygzier:v:22:y:2013:i:1:p:5-10
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    References listed on IDEAS

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    Cited by:

    1. Damian Stelmasiak & Grzegorz Szafrański, 2016. "Forecasting the Polish Inflation Using Bayesian VAR Models with Seasonality," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(1), pages 21-42, March.

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