The Effects of Shocks on the Real Economy in Romania. A Bayesian FAVAR Approach

The last five years have marked the global economy with a series of shocks, such as the COVID-19 pandemic, the war in Ukraine, supply chain bottlenecks, the surge in inflation, and the energy crisis, whose magnitude and duration were challenging to predict. Moreover, the impact of those shocks significantly affected the accuracy of macroeconomic forecasts. Thus, assessing the effects of the shocks became extremely important and conditioned by the econometric models that can capture a large amount of information. This paper proposes a Bayesian Factor-Augmented Vector Autoregressive Model (FAVAR) to assess the effects of the most prominent shocks that recently hit the real Romanian economy. We use a high-dimensional data set of quarterly indicators from 2005Q1 to 2023Q3, covering the real sector, price indexes, sentiment indicators and financial variables. Our main results suggest that tightening monetary policy shock decreases both the real economic activity and prices, while a supply shock produces a delayed negative and persistent effect on real economic activity and on the majority of the indicators introduced in the model. The results of the uncertainty shocks are characterized by wider confidence intervals and the effects are estimated to have a lower magnitude.