The article discusses two groups of problems in Russian statistics that still have no viable solutions. The frst one - the state of the statistics interface – is the set of channels through which users obtain statistical information. The second – metadata status – is the information on how the indicators are constructed. The problems are considered from the standpoint of consumers of statistical information, performing tasks of analyzing economic dynamics.

It is concluded that with the transition from traditional printed materials to statistical information systems, interface development has come to a standstill, and in the development of metadata, there is no compliance with any standards, uniformity, and consistency. In the author's opinion, these problems seriously hinder the improvement of all Russian statistics, being a kind of blood clots. When an interface becomes a bottleneck, the value of statistics to users decreases. The unsatisfactory state of metadata leads to the fact that consumers of statistical information are not always able to use it adequately, and the problems of statistical methodology are conserved.

The causes of the problems are determined, on the one hand, by the complex history of domestic statistics (extended period of development in a planned economy and the specifcs of economic transformation), and, on the other hand, by the lack of effective feedback.

The author considers possible approaches to addressing the problems. The expediency of creating groups of specialists in the structure of the statistical department on the main problem blocks, acting as points of growth and centers of competence, accumulating knowledge, mastering domestic and foreign experience, attracting representatives of the expert community, directing and controlling the activities to solve problems, is substantiated.

The growing importance of statistical evidence, data and information for political decisions is reflected in the handy and popular formulation ’Data for Policy’ (D4P). Under this cover, well-known guiding themes, such as the modernisation of the public sector, or evidence-informed policy-making, are led to new solutions with new technologies and infnitely rich data sources. Data for Policy means more to ofcial statistics than just new data, techniques and methods. It is not least a matter of securing an important function and position for ofcial statistics in the Policy for Data of the future. In order to justify this position, it is necessary to have a clear understanding of the tasks of ofcial statistics for the functioning of (democratic) societies, with a view to how these tasks have to be reinterpreted under changing conditions (above all because of digitisation and globalisation).

The article discusses specifc issues of the reliability of statistics on the spread of the coronavirus pandemic and the comparability of similar statistics across different countries. All countries faced challenges, regardless of the level of well-being and social system. However, the examples outlined in the article refer mainly to large economies, each of which for at least one year from 1980 to 2019 produced more than 1% of the global GDP. The organization of the health care system in these countries is different, and only the general requirements of WHO could provide information on the spread of the pandemic in comparable formats.

The authors formulated the problems of identifying those infected with Covid-19 and mortality statistics, indicating the various impact of the pandemic on deaths. It has been shown that the formal application of the WHO recommendations to the identifcation of infected persons and differences in the practical use of these recommendations in different countries can give poorly comparable results. The example of Russian statistics illustrates that it is possible to compare the operational data on the mortality of those infected with the coronavirus with the data on the total mortality in the country. Attention is drawn to the example of statistics from Germany, demonstrating the possibility of practical overlapping of the excess mortality rate and the operational data on the mortality of those infected with Covid-19.

Data on daily increments of infected, dead, and recovered per million people allows one to see the nature and prevalence rate of the pandemic in different countries in a comparable format. The largest single-day increase in coronavirus cases in some countries in 2020–2021 reached 2–3 thousand per 1 million population, while in others – it was less than 30. In most countries under review, daily deaths' peaks amounted to less than 40 cases, but there were other countries for which these peaks did not exceed 10 cases or less per 1 million population.

In conclusion, the report identifes six all-cause mortality factors associated with the pandemic and social distancing demands formulated by the American Institute for Health Metrics and Evaluation. According to the authors, it would be interesting to learn the experts' assessment of how realistic and benefcial it is to know how to keep track of these factors. It would improve the quality of international comparative analysis of socio-demographic indicators.

The article present results of the authors’ study of the social well-being of the Russian population – an assessment of the population’s health and attitudes towards a healthy lifestyle amid viral pandemic, based on materials of the Rosstat sample surveys of 2019 and 2020 and data from the All-Russian survey conducted by the Russian Public Opinion Research Center (VCIOM) on 27 September 2020. The authors described the transformation of living conditions in the light of the complex epidemiological situation and the increase in coronavirus cases among the population. Changes in the health status of the Russian population were analyzed by individual age groups.

The article assesses the strength of the relationship between the social well-being of the population by selected socio-demographic groups and the period of self-isolation, quarantine, or other restrictions imposed during the coronavirus pandemic in 2020. To solve this problem, demographic and socio-economic characteristics of respondents are presented, the distribution of responses according to the survey results is estimated, and the most signifcant factor characteristics are selected. Respondent replies were grouped according to the selected questions, including in the territorial context (by federal districts). To determine the strength of the relationship between the respondents' answers to the question and their gender or age distribution, the coefcients of mutual conjugacy and rank correlation coefcients were calculated and analyzed.

Analysis of the changes in the social well-being of population for 2019–2020 and the assessment of the strength of the relationship between the discussed indicators (gender, wealth, territory of residence) revealed the parameters that form the differences. After comparing the health status of the Russian population as a whole and by age groups in 2019 and 2020 based on data of sample survey on population health status, the following points were identifed. With the expected assessment of the population health status in the age distribution (deterioration in the older ages and better health in the younger ones), it also remains unchanged that more than half of the respondents characterize their health status as «very good» and «good». Noteworthy is the fact that the assessment of the health status of the Russian population has improved during the year. It is evidenced from changes in the structure of respondent replies, even though population health status survey of 2020 was conducted in the middle of lockdown amid the continuing negative trends in coronavirus morbidity and mortality.

The article analyzes the short-term effects of aggregate economic sentiment on the expected GDP growth in Russia based on the results of regular large-scale surveys of business activity of the Federal State Statistics Service (Rosstat) for the period 1998–2021. The main purpose of the study is to substantiate the predictive value of the opinions of economic agents in expanding macroeconomic information, especially during crisis periods. The authors aggregate quarterly information for the analyzed period on 18 indicators of surveys with a sample of about 24,000 organizations in basic kinds of economic activity and 5,000 consumers in all Russian regions in a composite economic sentiment indicator (ESI). Then, a statistical analysis of the time series of ESI and GDP growth is carried out, including the identifcation of the integrability order with testing for stationarity and the presence of causality between indicators. The authors prove the possibility of using a vector autoregression (VAR) model with dummy variables to measure the investigated relationship.

The forecasting results reflect the interconnection of two time series with the response in the dynamics of the estimated variable (GDP growth) to the reaction of the business environment and the simulation of fluctuations in the ESI dynamics, which are set by the authors and correspond to the expected economic sentiments amid possible crisis changes. Probabilistic estimates of GDP growth until mid-2022 are based on scenario impulses in the ESI dynamics at the 3rd quarter of 2021, which differ in the amplitude and duration of their impact on economic growth, primarily due to coronavirus shocks. According to the results, under all scenarios for the development of business trends introduced by the authors, national economic growth can exceed by the middle of 2022 the pre-pandemic level of the 4th quarter of 2019 (102,9%).

The article deals with several relevant socio-demographic issues in the largest by territory constituent entity of the Russian Federation – the Republic of Sakha (Yakutia), based on Rosstat data and information arrays obtained in the course of sociological study conducted in 2019 and 2020 by the staff of the Department of Geo-Urban Studies and Spatial Demography of the Institute for Demographic Research (IDR FCTAS RAS).

The introduction notes the relevance of the study and methodological approaches to the analysis of the problems under review.

The frst part of the article describes the general economic and socio-demographic situation in the region. It demonstrates how the industry specialization of Yakutia determines the socio-economic policy in the region. It is noted that the developing mining industry, along with the construction of large infrastructure facilities, requires an influx of labor resources.

In the second part of the article, after formulating the concept of sampling within the framework of a sociological survey (a model using key characteristics of the general population, based on the principles of quota-proportional and territorial methods), the social status of the population, its migration moods, attitudes towards labor migrants from abroad are analyzed, as well as the economic situation in general and the dynamics of the development of key enterprises in the region.

It is argued that, despite the active industrial development of the Republic of Sakha (Yakutia), the existing socio-economic problems in the future may influence the pace of spatial development of the region. First and foremost, it is a problem of migration outflows. Although the demographic indicators at the republic level are high, there is a division of the region's territory into a decreasing periphery and a growing centre. As in most other constituent entities of the Russian Federation, in Yakutia, there are processes of population concentration in the most prospective areas.

The authors drew up conclusions and proposals which, in their view, offer a targeted approach to developing programmes on improving the quality of life of the local population, establishing compensatory mechanisms in various spheres, taking into account the huge territory of the republic and its severe climatic conditions

The introduction of digital technologies in the monitoring and management activities of organizations is an important tool for the transformation of economic system at modern phase of the latest industrial and technological revolution. Currently, there is no unifed methodological apparatus for describing the state and development prospects of digital transformation. The analysis of objective patterns of the digital transformation of the Russian economy can be carried out by constructing mathematical and statistical models that make it possible to analyze the stages of digital maturity in the past and to determine the future development of projected digital phenomena.

The purpose of this article lies in modelling and forecasting of dynamics of digital transformation of the activities of organizations.

Digital transformation was measured based on indicators of the use of information and communication technologies in organizations, namely: Internet connection, website, purchase of goods and services via the Internet, use of software tools of the ERP, CRM, SCM class.

Growth curves are one of the most common tools for modeling technological development trends. For each time series, the accuracy of four models of growth curves was assessed: the Gompertz, Weibull's, logistic and log-logistic.

The practical application of this study is that the proposed approach can be used to assess trends in ICT diffusion in organizations by type of economic activity and by size to obtain a more complete characterization of digital maturity and further prospects for digital transformation of the Russian economy.