The Mechanism of Multifactor Assessment of the Optimal Tax Burden in the Context of Ensuring Inclusive Economic Growth in the Republic of Armenia

The article aims to study the ways and possibilities of optimizing the tax burden (tax to GDP ratio) in the economy of the Republic of Armenia, taking into account the influence of macroeconomic fundamentals, institutional factors, and about two dozen indicators characterizing inclusiveness. Within the framework of the study, a panel regression model was developed that describes the interrelations of the specified factors, which made it possible to trace the problem and identify the main trends and established patterns in the movement of the tax burden in 193 countries. In this context, the established trend of the tax burden in the Republic of Armenia in the period 2002-2022 was analyzed, according to which the actual level of the tax to GDP ratio until the mid2000s was below the optimal level calculated by the model, while in the period 2006- 2022 the opposite trend turned out to be decisive: the actual level of the tax burden constantly exceeded the optimal level calculated by the model. Based on the simulation analysis, a forecast was made and a policy scenario was developed, the implementation of which, taking into account the selected macrofundamental factors of inclusiveness and the desired indicators of the institutional environment, will ensure the achievement of the set goal in the medium term. Within the framework of the research, another panel regression model was used to assess the dependencies between the tax burden and the size of the informal sector of the economy in 122 low and middle-income emerging countries, including the Republic of Armenia. According to the results of the model, the increase in the tax burden leads to the strengthening of the motivation of economic agents to move and operate in the informal sector. This circumstance also indicates that the toolkits of fiscal policy should be adjusted by the target of ensuring the optimal tax burden.