The paper uses the data of digital tax burden calculator of Russia’s Federal Tax Service to study the determinants of the total tax burden and average salary on the example of St. Petersburg for year 2020 with enterprises broken down by size and types of economic activity and with the focus on top-priority and socially important industries. Therefore, this study aims to provide a mathematical substantiation for the need to improve state support measures provided for top-priority or socially important types of activities in the region using taxation means and methods. The objectives set were achieved using simulation modeling. The dependent variables that characterize the state support of the top-priority and socially important types of activities are the rate of tax burden (excluding mineral tax and excise taxes) and the size of the average salary. Moreover, two analyses were conducted sequentially to achieve the objectives. The first was a two-way analysis of variance of the relationship between the average salary and the size of the organization or industry as well as the dependence of tax burden on the same factors. The second was a one-way analysis of the variance of the tax burden and average salary depending on different types of activities as well as the scale of the enterprise. The results of the one-way analysis were refined through regression methods based on dummy variables. It was observed that there were no considerable differences between the average salary and total tax burden in top-priority or socially important sectors compared to the other industries in the economy. The trend was the evidence of insufficient support provided by the state and the need to introduce additional preferences.