Статьи

For countries focused on the extraction and processing of natural resources, including Russia, a crucial task is to ensure the rational extraction and distribution of natural rent. The tax model applied to natural rent should facilitate its optimal allocation to the budget without undermining the motivation of resource users to invest. This study seeks to gauge the extent of oil rent extraction into the Russian budget and suggest strategies to enhance the efficacy of redistributing oil rent to the state budget. Our hypothesis proposes that export customs duties, compared to the mineral extraction tax, prove more effective in achieving the desired redistribution from resource users to the budget. To assess the extent of oil rent extraction, we devised a methodology based on calculating the oil rent generated in Russia. This method
involves measuring the difference between the income generated by the oil industry and the total expenses incurred by oil sector companies. Our analysis reveals that, from 2005 to 2022, up to 87% of the oil rent generated in Russia was extracted through rent payments to the state budget. However, in recent years, the degree of oil rent extraction has decreased to 56%. This decline can be attributed to the tax maneuver initiated in Russia since 2015, entailing a reduction and eventual elimination of export customs duties, coupled with an increase in the mineral extraction tax rate. Our results indicate a diminishing effectiveness of rent-based taxation in Russia due to the reduced fiscal significance of rent payments. Furthermore, their regulatory function, designed to incentivize taxpayers for investment contributions, has weakened. These
findings offer valuable insights for shaping fiscal policies and lay the groundwork for further research in this domain.

The article deals with the evaluation of the impact of real estate tax reforms on their tax burden in the Czech Republic in the years 1993–2024. Real estate tax is one of the direct taxes, and in comparison, with income taxes, its importance lies mainly in providing income for local budgets. The unit type of tax rate specifically determines real estate rates. Facts, that tax reform in the area or real estate tax are minimal, the tax burden is often decreasing. As the tax burden decreases, so does the tax revenue. However, when tax reform occurs, this reform is often characterized by a significant increase in the tax burden. This is also evidenced by the last implemented tax reform in 2024 when rates increased by approximately 80%. The previous tax reform occurred in 2010 and increased rates by 100%. Despite this increase, the real tax burden decreased compared to the first analysed year 1993 and the last year 2024. The results of the regression analysis show that inflation is the factor that negatively affects tax revenue. To minimalize a decrease in tax revenue from 2024, a provision containing an inflation coefficient is implemented in the legislation as part of the 2024 reform. Conversely, a reduction in the tax burden was not found for real estate intended for permanent housing in small municipalities with up to 600 inhabitants. On the contrary, there was an increase in the tax burden. Scientific methods such as analysis and comparison, as well as regression and correlation analysis are used to achieve the paper’s goals.

This research investigates the Russian stock market response to COVID-19 pandemic and compares how the reactions to it varied among the industries. The event study and Wavelet coherence were applied to answer the research question. It was discovered that the Russian stock market in general had a strong negative reaction to the COVID-19 outbreak.

However the response to the fi rst case was stronger than the response to the fi rst COVID-19
related death. It was also discovered that most of the industries reacted to the pandemic in line
with the overall negative reaction of the market, with transportation and fi nancial sectors demonstrating the most strong response. The returns of the different sectors showed high coherence during the fi rst wave of the pandemic that is another fi nding. However, the chemical sector reacted rather moderately to the COVID-19 and demonstrated lower coherence with the other sectors during the fi rst wave of the pandemic, so it might be benefi cial to include the stocks of the chemical companies in the portfolio for its diversifi cation. The results obtained have practical value for the investors (in terms of portfolio construction) and governmental regulators that are trying to mitigate the impact of the shocks on the stock market.

A survey of recent data permits an overview of the world and Russian markets for gallium and its compounds after the crisis of 1999-2001.

The outstanding Russian soil scientist N.M. Tulaykov lived and worked at the beginning of the twentieth century, and made a great contribution to the scientific basis of agriculture in southern Russia. Coming from the poorest peasant family, he received an excellent education and worked with other eminent scientists. In 1908-1910 he was sent on a scientific and practical trip to the USA, Germany and Britain. In 1910 he was appointed as a director of Bezenchukskaya agricultural experiment station. From 1915 he headed the Agricultural Chemical Laboratory in Petrograd; from 1918 he was a Chairman of the Agricultural Scientific Committee at the Russian Ministry of Agriculture. From 1920 to the end of his life he headed the field-growing department at Saratov experimental station and was a professor at Saratov Agricultural Institute. He developed and promoted the dry farming system to combat famine (including famine in the Volga region in 1921-1923). He was unjustly repressed and died tentatively in 1937-1938 in the Solovki or in prison in Saratov.

The paper considers a new method for finding patterns in a chaotic system and an algorithm implementing it that automatically computes geometric, physical, and other possible interactions based on preferences between objects in a chaotic system in a reasonable computational time, selecting the only possible solution from the whole population. The algorithm has P-class simplicity in solving NP-class problems, bringing machine intelligence as close as possible to human intelligence. Descriptions of original solutions to a number of technical and creative problems are presented.

There are the main points of the derivation of the differential equations of the Earth’s rotational motion. The periods of oscillation of the Earth’s axis are grounded by the angular momentum theorem. The constants of the equations, the initial conditions, and the theory of their computations are discussed. The results of integrating the equations over time intervals from 0.1 year to 1 million years are considered. The theory of solutions transformation to the mobile plane of the Earth’s orbit is considered for millions of years, and the solution results are presented at different time intervals from 100 years to 20 million years. The evolution of the Earth’s axis is analyzed. It is established that the Earth’s axis precesses with respect to a fixed direction in space, which differs from the direction of the precession of planetary orbits. Physical explanations of the received oscillations of the Earth’s axis from 14.68° to 32.68° are given. The oscillations of the Earth’s rotation period are shown. Evidence of the reliability of the solutions obtained is presented. The work is of interest to a wide range of researchers in the fields of astronomy, paleoclimate and geophysics.