Purpose of the research. The growth in domestic grain exports is one of the key factors in the positive development of the country’s economy, which is due, among other things, to the growing demand for this product in various regions of the world. Therefore, Russian exporters are focused on implementing a strategy aimed at strengthening their position in the international market. However, there are a number of factors that can influence grain export volumes, either upward or downward, which negatively affects both revenues andthe willingness of exporters to ensure conditions for export cargo flows in line with market needs. Therefore, the purpose of this paper is to construct and solve a forecast model, the application of which will enable the most accurate planning of exporters’ resource potential.

Materials and methods. To achieve this purpose, statistical data over a relatively long period (27 years) were used. Statistical and correlation-regression analysis methods were used in developing the dynamic econometric model. This allowed us to explore the relationships between variables, as well as establish the structure and test the time series for cointegration. The model solution uses the least squares method, which involves checking it for compliance with the relevant requirements.

Results. Using a matrix of paired correlation coefficients, intercorrelated variables were excluded, and the most significant factors for forecasting were identified. It has been established that the closest possible connection exists between the level of Russian grain exports, gross volumes of grain production, global grain export volumes, and global grain shipments. Given the relatively strong intercorrelation between global grain exports and global grain shipments, the authors decided to include the global grain export index in the model. To eliminate “spurious” correlation, which could be caused by trends and periodic fluctuations, a study of the time series structure of the indexes was conducted, not only visually but also using autocorrelation functions. As a result, a model was constructed for the dependence of Russian grain exports on gross production volumes in Russia and global grain exports. Tests confirmed the adequacy of the relationships between the indexes. The construction of the model made it possible to quantify the effect of factor features on the change in the result: an increase in grain production by 1 million tons leads to an increase in grain exports by an average of 313 thousand tons, while an increase in global exports causes an increase in Russian exports by 109 thousand tons.

Conclusion. To validate the econometric model, actual and forecasted factor values were substituted into it. The forecast values obtained as a result of applying the author’s model almost completely coincided with the forecast made by the Food and Agriculture Organization of the United Nations for 2025, demonstrating its adequacy.

Subject. A complex of relations for assessing the operation of the fire safety system in Russia, the Southern Federal District (SFD), and its regions. This system is a broad structure of bodies and organizations, integrated to solve the problems of ensuring the safety of the population and the sustainability of the country’s economy and its regions. The effective operation of such a system requires adequate statistical information support, as it is the only source of obtaining complete, reasonable, and timely data on the stress and variability of fire hazards.

Purpose. To obtain real information about the complex and multifaceted processes of fire safety at the federal and regional levels in modern Russia.

Methodology. The study is based on the integration of information about the number of fires and their material damage indexes in the Southern Federal District and its regions, as well as in Russia as a whole. Its main element is the determination of trends in dynamics and the comparison of these trends at the studied national economic levels for the period 2018 - 2024. The article compares the obtained trends to receive a real picture of fire safety in the most dangerous and safe regions of the Southern Federal District, as well as to determine whether these trends correspond to the national trends.

Results. Based on statistical data, some trends in the growth of the number and material damage from fires in the country and the Southern Federal District have been identified, as well as the regions of this federal district where such negative trends are most pronounced, and the regions where the fire hazard is decreasing.

Conclusions. The slight increase in the number and material damage from fires necessitates the improvement of the entire fire safety system. At the same time, first of all, such improvement should concern information support based on the widespread introduction of statistical processing methods that allow considering both individual fires and analyzing fire hazard in the form of a process at macro and meso levels of socio-economic development.

The purpose of the study. The purpose of the study is to analyze the state and dynamics of fixed assets in the tourism and hospitality industry using statistical data analysis and forecasting methods.

Materials and methods. The information base was the Rosstat database in the context of the activities of enterprises in the field of hospitality and catering. Statistical analysis methods are used: analysis of dynamics, structure, coefficient analysis, correlation analysis, index method, forecasting. The prediction was carried out by constructing an ARIMA model. Calculations and estimation of Pearson pair correlation coefficients, Grainger causality estimation are performed. The initial data were previously brought to a stationary form using the TRAMO/SEATS procedure. The study period is 2020–2024. The following system applications were used: MS Excel, Gretl.

Results. The capitalization of non-current assets in the tourism and hospitality industry has increased more than fourfold over the period under review. The largest increase was observed in the “structures” group, the smallest – in the “non–residential and residential buildings and premises” group. The presence of significant structural shifts in fixed assets and the lack of identity in the compared structures were revealed. The rate of renewal of fixed assets significantly exceeds the rate of their disposal. The degree of depreciation of the entire set of fixed assets in the industry is relatively low, while it slightly exceeds the average values for the economy as a whole. The “machinery and equipment” group is characterized by the highest degree of depreciation, while the “non–residential buildings” group is characterized by the lowest. The capital-labour ratio index shows a decrease with a simultaneous increase in the capitalization of fixed assets, which is due to the lag in the dynamics of the material and technical equipment of the tourism industry behind the index of staffing. There is an increase in the efficiency of the use of fixed assets, characterized by an increase in the fixed assets turnover ratio. The index of profitability of fixed assets shows a mixed trend in dynamics: a decrease until 2020, and an annual increase from 2021. There has been a significant increase in capital investments in the tourism segment of the economy. It has been stablished that the real volume of investments in the industry is lower than planned. A high and direct relationship was recorded between the variables “return on fixed assets” and “financial result”, direct and noticeable – between “investments” and “profit”, “depreciation” and “investments”. The Granger causal relationship was recorded between the following variables: “investments in fixed assets” (cause) and “depreciation of fixed assets” (consequence), “availability of fixed assets” (cause) and “depreciation of fixed assets” (consequence).

Conclusion. The authors concluded that the tourism and hospitality sector, despite a series of successive crises, is actively developing, due to the growing capitalization of assets and increased efficiency of their use. The results obtained can be useful for government agencies and private investors to manage the industry.

The purpose of this research consists in the identification and systematization of approaches that explain the variability of the structure of the creative economy as a set of economic activities.

Materials and methods. The study of the variability in the structure of the creative economy is based on reports from the Department of Culture, Media and Sport of the United Kingdom (1998) and international organizations (1986, 2008, 2009, 2025), as well as on the methodology of Rosstat. The main method of structure analysis of the creative economy is intended to summarize the positions of both government and international organizations, as well as researchers in this field. The empirical basis of the study is the time series of added value of the creative economy, the share of added value in gross domestic product, indexes of the physical volume of added value of the creative economy in 2017–2025, as well as the added value of economic activities by class.

Results. The presence of groups of economic activities, representing the “core” of the creative economy has been revealed: groups related to natural and cultural heritage, music and performing arts, production of creative goods, publishing, television and radio, creative services (design, advertising and architecture). Groups of activities have been identified that are considered only in one of the classifications and represent a possible direction for the development of the creative economy: goods partially classified as creative, trade, wholesale and retail, creative benefits, rental and leasing in this area. Empirical assessment of the dynamics of the added value of the creative economy presents a significant difference in growth rates and volume indexes both in individual periods and for the entire period under review between the types of economic activities related to the informatization of individual processes and the other groups that make up the creative economy.

Conclusion. The change of the standard classifications, used to aggregate statistical data makes possible to more accurately assess the contribution of the creative economy in macroeconomic indexes. However, the creative industries included in the creative economy have different importance in its structure and show significantly different growth rates. The analysis of the existing classifications of creative industries provides an understanding of such differences and possible trajectories of transformation of the structure of the creative economy.

The purpose of the study is to develop a methodology for calculating adjustments from the objects of comparison to the object of assessment, based on data on completed transactions. Price adjustments of similar objects are used in the quantity adjustment method. According to the authors, this method is outdated and will gradually be replaced by modern methods of data analysis. However, today it is most popular among independent appraisers due to its simplicity and established tradition. Thus, there is a need to provide evaluators with tools that allow combining traditional and modern calculation methods. One of the ways to determine quantitative adjustments is the method of paired sales (comparisons). Pairwise comparisons are supposed to search for objects that differ in the value of one characteristic. The disadvantage of this method is the difficulty of finding such objects and the lack of a priori information about the reasons for the difference in prices. The observed difference in properties do not automatically affect prices. When working with small samples, one can encounter the observed and even statistically significant effect of the “influence” of a particular feature on the price of an object, since small samples do not ensure the stability of the results of statistical conclusions within the frequency approach, which is traditional for appraisers. Remember the rule “correlation does not imply causation”. Most often, the problem of accounting for false connections disappears as the volume of the analyzed sample grows. Thus, the problem of ensuring that only those differences in the properties of objects on the market that actually affect prices are taken into account can be solved, first of all, by increasing the amount of analyzed data. For a long time in the domestic theory and practice of evaluation, mainly offer prices available from advertisements in listings are considered. The results obtained on their basis, including coefficients that can be used as adjustments, always have elements of subjectivity, since only the expectations of sellers are reflected in the prices of proposals. Therefore, we have to study the conditions for the transferred property rights, the conditions of a possible transaction, the “marketability” of the transaction, etc. With the opening of Rosreestr data on completed and registered transactions, new opportunities for data analysis appear, including for calculating adjustments, at least for those pricing factors that are entered into the Rosreestr database when registering transactions.

Materials and methods. The article uses open data of Rosreestr on completed and registered transactions. The main research method is the A/B testing technique, which has proven itself in digital marketing. The method of calculating adjustments, discussed herein, is essentially a transfer of A/B testing to the theory and practice of real estate valuation. Calculations were performed in the statistical package environment R. Data preprocessing and mapping were performed in Python. The OpenStreetMap mapping framework was used.

Results. A methodology for calculating adjustments from comparison objects to the object of assessment by pricing factors included in the Rosreestr database is proposed. The technique is based on open data, is easy to reproduce and is brought to the software solution. It should be noted that the result of the article is precisely the method, and not the specific numerical values of the adjustments. The appraiser in person using data relevant to the specific task must perform all calculations.

Conclusion. Open data of Rosreestr can and should be used in real estate valuation tasks. They allow you to solve a number of evaluation problems that were previously inaccessible or difficult to resolve due to the lack of data on transactions. This gap in valuation theory and practice is gradually being filled with the introduction of open access to transaction data.

The purpose of the research. Improving the methodology for integral assessment of the level of digitalization of organizations, which allows for comparable spatial and temporal analysis at the level of regions, federal districts and the country as a whole.

Materials and methods. The study is based on the data from the Federal State Statistics Service for 2020–2024. The polygon method, adapted to solve the problem of integral estimation, is used as the main method. The evaluation procedure includes the formation of a system of 15 indexes, grouped into 7 thematic blocks, their minmax normalization, the calculation of local criteria as arithmetic averages and the determination of the integral index as the ratio of the area of the polygon of the region to the area of the polygon of the reference region.

Results. A methodology was developed and tested in which the key shortcomings of existing approaches were eliminated: sensitivity to outliers, subjective weighting, and reliance on a limited range of indexes. Based on this methodology, the level of digitalization of organizations across the Russian Federation’s federal districts was calculated for 2024. It was found that the highest level of digitalization of organizations is observed in the Central Federal District (35.2%), and the lowest – in the North Caucasus Federal District (16.6%). The average Russian index was 29.5%. The dynamics for 2020–2024 demonstrates an overall increase in the level of digitalization of organizations by 7.1 percentage points, despite the negative impact of external shocks.

Conclusion. The proposed methodology provides a comprehensive, quantitatively interpretable and visually illustrative assessment of the digital development of Russian organizations. The results can be used by government statistics and management authorities to monitor business digitalization, develop regional strategies, and equalize digital inequality between territories.