Natural Resources as a Key Factor in Forecasting GDP in Europe
Natural Resources as a Key Factor in Forecasting GDP in Europe

Author(s): Gildas Bondi, Sarah Goldman, Maya Jandah, Virginia Zhelyazkova
Subject(s): Social Sciences, Economy, Supranational / Global Economy, Business Economy / Management, Energy and Environmental Studies, Sociology, Policy, planning, forecast and speculation, Economic development
Published by: Университет за национално и световно стопанство (УНСС)
Keywords: mixed-frequency Bayesian VAR; GDP growth forecasting; performance; monetary policy tools; Brent and precious metals prices
Summary/Abstract: A Mixed-Frequency Bayesian Vector Autoregressive (MF-BVAR) model is developed in this work to forecast GDP growth in Europe. To improve forecast accuracy, the model incorporates data on natural resources, macroeconomic variables, and monetary policy instruments. The dynamic interaction between these factors is captured by the model through the integration of mixed-frequency data and Bayesian inference. Furthermore, we employ a Bayesian framework to integrate prior distributions and revise them with observed data, ensuring our model remains robust and adaptable to new information. By including data on natural resources, forecasting errors as determined by metrics such as Theil inequality coefficient and Root Mean Standard Errors (RMSE) can be reduced. The findings show how well the model predicts GDP growth, giving economists and policymakers important information.

• Details
• Contents