EMPIRICAL APPROACH TO GROWTH ANALYSIS – PECULARITIES FOR MODELING STRATEGY IN THE CASES OF BIG EXOGENIOUS SHOCKS

Empirical investigation on growth, especially in the course of big exogenous shocks is still relatively ambiguous. While models of developed economies describe the growth process as a smooth movement along the balanced growth path, this pattern is altered in the cases of big exogenous shocks that hit economies. The later accumulation of evidence, including the big shocks due to pandemic and Russia - Ukraine war led to more realistic specifications of growth models as well, putting the emphasize on the impact of shocks on growth processes. Hence, the main objective of this paper is to provide a review of the papers that investigate empirically growth and its main determinants, with the accent on analysis of the impact of shocks on growth patterns. A distinction is made between studies that investigate developed economies and those that concentrate on developing or transition economies. The former ones usually apply the modelling strategy based on the neoclassical linear framework and, their review offers valuable insight and overview of the variables mostly used in growth studies. On the other side, the studies concerning developing or transition countries are rather focused on finding new ways of empirically modelling growth in specific conditions of shocks. Although still the majority of the analyses are based on the linearity assumption, in this review we shall treat only the ones that introduce non-linearity in the growth studies, assessing the ways they address the non-linearity observed in the data generating processes. Finally, the proposed strategy for modelling big shocks in the growth pattern is adjusted growth accounting formula with Markov Switching Vector Autoregressive modelling. The modest number of variables is due to the intention of the empirical exercise to put a focus on the shifts in growth rather than on the detailed determinants behind the shifts. Additionally, it should be emphasized that the informative purpose of this empirical model is limited by the lack of data for other possible variables and by the modelling procedure.