ROLE OF DYNAMIC MODELING IN THE RESEARCH OF THE SHADOW ECONOMY

Abstract

Dynamic modeling of the shadow economy is becoming an integral part of modern economic analytics. It allows you to take into account the complex interrelationships and dynamics of the phenomenon of the shadow economy, which is critical for analyzing its impact on global financial and economic processes in the country and beyond. Using real-time data and intelligent algorithms helps identify changes and trends, which is key to predicting and managing in a changing economic environment. The purpose of this study is to consider and structure four types of dynamic mathematical models aimed at analyzing and forecasting the phenomena of the shadow economy of Ukraine in order to improve policies and management strategies aimed at reducing the negative impact of the phenomenon of informal economic activity on the economy of Ukraine and society. As a result of the research, the main methods of such dynamic models were considered: agent models (ABM), dynamic stochastic models of general equilibrium (DSGE), macroeconomic models, time series models; and how they relate to the shadow economy, and a comparative analysis of the application of these types of models to shadow economy simulations was conducted.