Economic systems are increasingly exposed to external shocks of various nature, which test their resilience. The tax system, which is directly linked to the level of business activity, is one of the first to experience stress, so the ways it reacts to shock are of particular research interest. The 2020–2021 coronavirus pandemic made such studies more acute. The purpose of the paper is to develop and test new approaches in studying the resilience of the tax system in terms of tax revenues by analyzing the dynamics and structure of the tax system stress index in the Russian Federation in pre-pandemic, pandemic and recovery periods. The tax system stress index for tax revenues is calculated as the difference between the moving standard deviation and the moving average growth rate of tax revenues. We have developed a method for decomposing the stress index by source with determining the contribution of each tax to the average growth rate and to the standard deviation of the growth rate. We have also calculated the Russian Federation tax revenue stress index from December 2015 to March 2022 and identified its sources. It was found that the stress indices for almost all taxes (except for excises and state duties) are significantly positively correlated with each other. The main contribution to the growth of the stress index during the crisis and its decline within the recovery period is made by profit tax and a group of taxes on natural rent, which significantly negatively correlate with oil prices. Under the pandemic crisis in Russia, the stress index on revenue form special tax regimes also increased significantly. It was found that the personal income tax has a stabilizing effect on the tax system stress index in the crisis and post-crisis periods. During the pandemic in Russia, the damping role of excises also came to the fore, which is explained by institutional factors and changes in tax rates. The research findings can be advantageous for the authorities to make an impact on the most vulnerable components of the tax system of the Russian Federation in order to increase its resilience to crises.
Research background: The research is based on the assumption that the sectoral structure of economy has a significant impact on the level and dynamics of sub-federal budget tax revenues. It distinguishes the following sectoral determinants of tax revenues in regions: the levels of tax return and tax absorption, inflation and economic growth in various economic activities. Purpose of the article: We aimed at assessment of contribution of economic activities and their determinants to the increase in tax revenues of sub-federal budgets of the Russian Federation in 2011–2015 compared to 2006–2010. Methods: Development of a four-factor additive-multiplicative model of the tax revenue formation in regions, application of the proportional and logarithm methods of factor analysis to assessment of contribution of various activities and their determinants to increase in tax revenues of sub-federal budgets, evaluation of inter-regional inequality of tax revenues growth based on the weighted coefficient of variation, and decomposition of this inequality using the A. Shorrocks technique. Findings & Value added: We identified activities that made the largest contribution to the increase in tax revenues of the Russian sub-federal budgets. We found that the inflation factor had a predominant positive effect on the growth of tax revenues, while the contribution of the economic growth factor was 4 times less; however, the situation in various activities differed significantly. Generally, changes of sectoral levels of tax return and tax absorption influenced negatively the regional tax revenues. In addition, they moved in opposite direction in the regions. Ultimately, the uneven change in tax returns and price levels in the mining and manufacturing activities of Russian regions made the greatest contribution to inter-regional inequality of the growth of sub-federal budgets tax revenues.
The paper examines the relationship between financial and industrial stresses in the Russian economy in 2006–2019, mediated by the monetary policy of the state. Stress indices are constructed on the basi of a number of financial market and industrial sector indicators of the Russian economy. These variables are aggregated using the principal component analysis. Stress indices are calculated as the moving difference between the standard deviation and the mean value of the first principal component. The graphical and correlation analysis confirms that industrial stress in the Russian economy grows during financial crises, accompanied by an increase in credit interest rates (including the key rate) and the scale of refinancing of credit institutions by the Bank of Russia. Based on the construction of ARDL models, we obtained convincing evidence of the positive impact of both a short-term increase in the key interest rate and a longer increase in the scale of refinancing of credit institutions by the Bank of Russia on the reduction of financial and industrial stresses in the Russian economy, which, however, appears in different time intervals. We concluded that the combined management of industrial and financial stresses, taking into account their interaction and sensitivity to different instruments, requires the search for the optimal combination of monetary regulation methods. The results obtained may be useful in conducting a prudent monetary policy in periods of financial instability.
Abstract. Government budget crises in the 2000s were magnified by the increase in tax revenue volatility governments experienced. Governments can decrease the variance of their tax revenues by holding the efficient "portfolio" of taxes. In this conceptualization, each tax base is a potential asset the government can hold and the tax rate on a given base is the weight they put on the asset. Conceptualizing government finances as an optimal portfolio problem highlights the ability of governments to hedge risk by taxing different bases, but this method must be adapted to account for numerous differences between a government and an individual investor. This paper conducts the analysis of the mean-variance tradeoff made by governments within a utility framework. This analysis demonstrates the tradeoffs governments face between volatility and deadweight loss and between public and private consumption volatility. Therefore, the government does not minimize tax revenue volatility but aims to optimize tax revenue volatility. As an application of the theoretical model, I create a method to estimate the minimum variance a government can achieve for a given expected level of tax revenue: an efficient frontier. I demonstrate the method with a few examples using data from U.S. state governments. Estimating state-specific efficient frontiers allows for across state analysis of the relative mean-variance tradeoffs. In addition, the different portfolios states have held can be plotted to determine how state portfolios have changed over time relative to the efficient frontier.JEL Numbers: H21, H7, H68, R51
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