The paper studies the role of data as an economic asset in the digital economy. The research is focused on the development of an approach to comprehensive data valuation and their adequate treatment in macroeconomic statistics.
The first part of the paper reviews the major publications on the so-called Solow productivity paradox: the impact of digital technologies on the productivity growth slowdown. Considering points of view of various researchers, the author takes an opinion that the existing statistical methodology does not permit comprehensive measuring of the digital economy contribution to the productivity dynamics. At the same time, the author does not support the proposal to include the value of data generated by unpaid household activities in macroeconomic accounting and expand the scope of key macroeconomic indicators such as GDP.
In the second and the third parts the methods of data valuation used by companies as assets in production, as well as major discussed proposals on methods for measuring the value of data in macroeconomic statistics, are considered. These two aspects of data valuation are closely related, both informationally and methodologically. The author concludes that an increase in the need for the valuation of data at the micro level will inevitably lead to corresponding changes in the methodology of macroeconomic statistics.
The last part of the paper explores more elaborately the issues of data valuation as a non-produced asset. The need for such an approach is caused by the existing gap between the marketed assessment of the contribution of data to production and the existing possibilities for accounting for them at the costs of their production. In the author’s opinion, this is a promising direction, allowing to overcome the indicated gap. In support of this, the article provides examples of experimental calculations based on IFRS reports of four Russian companies involved in the production of digital services.
Experimental valuation of non-produced assets using the net present value method shows that the value of the non-produced assets involved in the production of data-driven companies differs from the values recorded in their financial statements. This, in particular, occurs due to the underestimation or overestimation of the value of the data used in production, which, according to the author, constitutes the bulk of the unidentified unproduced assets of digital companies.
The author concludes that the development of methods for accounting for the value of data as a non-produced asset used in the production of digital products is one of the priority tasks of developing the methodology of the system of national accounts.

The article reflects the results of a study of the impact of migration on regional labour markets amidst a decline in the working-age population in Russia. After substantiating the relevance of the issues under consideration, the authors propose a methodological analysis toolkit, the author’s own methodology for calculating the coefficients of permanent long-term external and internal labour migration in regional labour markets, and the coefficient of total migration burden. In addition, the authors provide an overview of the information and statistical base of the study. According to current migration records, data of Rosstat sample surveys on Russian labour migrants leaving for employment in other regions, regional labour resources balance sheets based on the calculated coefficients of labour market pressures, the authors analyzed the impact of migration on the Russian regional labour markets over the past decade.
It revealed an increasing role of internal labour migration in many regions, primarily in the largest economic agglomerations and oil and gas territories. At the same time, the role of external labour migration remains stable and minimum indicators of the contribution of permanent migration to the formation of regional labour markets continue to decrease. It has been established that irrational counter flows of external and internal labour migration have developed, which indicates not only an imbalance in labour demand and supply but also a discrepancy between the qualitative composition of migrants and the needs of the economy.
It is concluded that the state does not effectively regulate certain types of migration, considering its impact on the labour market. The authors justified the need for conducting regular household sample surveys according to specific programs to collect information about labour migrants and the conditions for using their labour. In addition to the current migration records, using interregional analysis, this information allows making more informed decisions at the federal and regional levels to correct the negative situation that has developed in the regional labour markets even before the coronavirus pandemic had struck.

The topic of quantitative research on informal employment has a consistently high relevance both in the Russian Federation and in other countries due to its high dependence on cyclicality and crisis stages in economic dynamics of countries with any level of economic development.
Developing effective government policy measures to overcome the negative impact of informal employment requires special attention in theoretical and applied research to assessing the factors and conditions of informal employment in the Russian Federation including at the regional level. Such effects of informal employment as a shortfall in taxes, potential losses in production efficiency, and negative social consequences are a concern for the authorities of the federal and regional levels. Development of quantitative indicators to determine the level of informal employment in the regions, taking into account their specifics in the general spatial and economic system of Russia are necessary to overcome these negative effects.
The article proposes and tests methods for solving the problem of assessing the impact of hierarchical relationships on macroeconomic factors at the regional level of informal employment in constituent entities of the Russian Federation. Majority of the works on the study of informal employment are based on basic statistical methods of spatial-dynamic analysis, as well as on the now «traditional» methods of cluster and correlation-regression analysis. Without diminishing the merits of these methods, it should be noted that they are somewhat limited in identifying hidden structural connections and interdependencies in such a complex multidimensional phenomenon as informal employment.
In order to substantiate the possibility of overcoming these limitations, the article proposes indicators of regional statistics that directly and indirectly characterize informal employment and also presents the possibilities of using the «random forest» method to identify groups of constituent entities of the Russian Federation that have similar macroeconomic factors of informal employment. The novelty of this method in terms of research objectives is that it allows one to assess the impact of macroeconomic indicators of regional development on the level of informal employment, taking into account the implicit, not predetermined by the initial hypotheses, hierarchical relationships of factor indicators.
Based on the generalization of the studies presented in the literature, as well as the authors’ statistical calculations using Rosstat data, the authors came to the conclusion about the high importance of macroeconomic parameters of regional development and systemic relationships of macroeconomic indicators in substantiating the differentiation of the informal level across the constituent entities of the Russian Federation.

This publication reflects the results of the authors’ research aimed at finding ways to reduce the complexity of appraising the investment attractiveness of potential recipients of investments. The purpose of the research is to create a methodology that will effectively manage not only the process of determining the recipients of investments but also the development of organizations to increase their investment attractiveness.
The authors provide an overview of the most significant publications that consider existing methods for appraising investment attractiveness, based on both financial statements and the market value of a business.
In the main part of the article, the authors conclude that data envelopment analysis (DEA) may be used to aggregate several different criteria of the investment attractiveness appraising in one number. The section that presents the empirical results of the study contains a description of a number of indicators of Russian oil refining companies and their aggregation based both on the method of expert assessments and a formal approach using the DEA. The examples only apply criteria calculated based on organizations’ financial statements.
It is emphasized that in real practice the first method is a very expensive and time-consuming procedure in comparison with the second, which provides a formalized agreement of the criteria used in the former method, and takes into account the situation in the entire market segment under study.
It is shown that the calculations made based on these two methods give approximately the same results. This indicates that the methodology proposed by the authors can be considered as an effective alternative to existing expert approaches to appraising investment attractiveness.
In the final part of the article, recommendations are formulated for improving the proposed methodological approach by including a number of market indicators that characterize the activities of potential recipients of investments.

This publication reflects the results of the author’s research on improving the domestic statistical and methodological tools used in the analysis and forecasting of the Russian economy. In this regard, the main features of the formation and application of the Business Activity Index for basic spheres of the economy of the Institute of Economics of the Russian Academy of Sciences (hereinafter, the index of business activity) are shown and substantiations of its individual advantages are given in comparison with the index of output of goods and services for the basic types of economic activities of Rosstat (hereinafter, the release of goods and services). The authors provide evidence that despite a number of positive qualities of the applied methodology for constructing the index of output of goods and services, the business activity index, according to the authors of the article, provides a more objective assessment of macroeconomic dynamics, since it includes additional indicators reflecting financial and social aspects of economic development. It is proved that the main advantages of the business activity index are manifested in a more accurate determination of the depth of crisis phenomena in socio-economic development, as well as in determining the timing of the onset and overcoming of these negative processes.
The characteristics of the macroeconomic indicators that make up the business activity index are given. Methods for calculating the weights of indicators characterizing the level of business activity in various spheres of the national economy, as well as methods for determining changes in this level are considered. Changes in the dynamics of these weights are analyzed. Ways of more efficient use of business activity indices in the practice of accounting, forecasting and management of socio-economic development are proposed.
The conclusion is substantiated that it is advisable to use the business activity index for macroeconomic analysis, forecasting and strategic planning, which will make it possible to more accurately assess the impact of the implementation of national projects and the social package of the message of the President of the Russian Federation on economic growth and increase the efficiency of using business activity tools in the practice of public administration of social economic development of the country.

The article presents the authors’ ideas regarding the measurement of the effectiveness of the proposed modernized version of the progressive taxation scale.
The comparative statistical and economic analysis of taxation of individuals carried out in the article showed that in most countries with developed market economies, a progressive taxation scale is used, which allows taking into account population ability to pay and the established subsistence minimum. At present, Russia is practically one of the developed countries in which a flat scale has remained. But recently, in our country, measures are being taken to introduce some elements of progressive taxation. The paper also shows that a significant drawback of the progressive scale used in different countries is the abrupt change in the size of the tax. It is proposed that, the so-called «piecewise-linear» model of the progressive taxation scale that from the taxpayer’s perspective is fairer, be used.
Using statistical data, the authors demonstrated the advantages of the proposed «piece-wise-linear» model of the progressive taxation scale in comparison with the «flat» scale. The «piecewise linear» scale proposed in the study will allow individuals (taxpayers) to make an easier transition to a progressive tax rate. To assess the effectiveness of the proposed version of the «piecewise-linear» taxation scale, an economic and mathematical model has been developed, which implies tax exemption for persons with incomes below the subsistence level and an increase in the tax rate, compared to the existing one, for persons with large incomes. The model was tested on data of Rosstat on the income of individuals.
The introduction of «piecewise-linear» taxation scale will, in authors’ opinion, increase tax collection and more fully implement the distribution function of taxation, which will ultimately stimulate the development of the economy and social sphere.

The article focuses on determining the unique features and intensity of Covid-19 spread in large economies, using mathematical and statistical tools. According to international statistics and using the example of 24 countries, each producing more than 1% of the world GDP at least one year between 1980 and 2019, the author carried out a preliminary analysis of geographical distribution and spread of the viral pandemic, that in 2020 overtook almost the whole world.
It is suggested the data for these countries be grouped into three types of scenarios, dividing them into several options. The work uses time series for three indicators, calculated per 1 million of the country’s population. Two of these indicators reflect, respectively, the levels of infection and incidence of coronavirus cases, and the third - daily growth of COVID-19 cases. Such a system of indicators allows, according to the author, to adequately determine emerging trends and is convenient for comparing the unique features and intensity pandemic spread in different countries.
The article presents a hypothesis about the possible reasons for the synchronization of trends for different countries in which the same type of scenario came true. It is demonstrated that the often-used case-fatality rate is not very informative in conditions when the pandemic is far from ending. A more illustrative indicator of healthcare system mobilization capacity as a whole in the face of global challenges is the infection fatality rate per 1 million of the country’s population. The ranking of all 24 countries by this indicator significantly differs from the Global Health Security Index ranking, published in 2019.
After the conclusion, in the appendix to the article, the author provides illustrations in the form of graphs tracking the pandemic spread in the countries under review, as well as brief information on particular aspects of the Republic of Korea response to managing and combatting the most dangerous infection, which is different from both temporary but harsh restrictive measures for the population in the PRC and relatively mild measures implemented in many countries of the world.

The article examines publication of statistical data commemorating the anniversaries of the USSR Victory in the Great Patriotic War as the most important information sources for an objective analysis of historical events. The reason for writing this article was the release of the statistical handbook of Rosstat, dedicated to the 75th anniversary of the Great Victory. In the introduction, the author argues the current urgency of issues addressed in the article caused by information warfare aimed at distorting the historical truth about the role of our country in the anti-Hitler coalition and the defeat of fascism in the World War II. The body of the article describes the concept and content of the anniversary edition. An important point of the article is the analysis of data sources used in the preparation of the handbook.
The author reviews the anniversary handbook structure that includes a preface and the following sections: Population, Economic, Living conditions, Mobilization of population, Partisan movement, Evacuation during the war, Casualties and losses during the war, Military memorials and cemeteries, State awards, References. It is noted that the handbook maintains the tradition of previous statistical publications dedicated to the anniversaries of the Great Victory. Lastly, the author substantiates the novelty of data presented in the anniversary handbook and the logical structure of statistical materials in it.
The author draws conclusions about the paramount importance of, and need to continue popularization of data on the great exploits of the Soviet people during the war and to introduce new statistical information into scientific circulation, which is causing further comprehension of primary information sources about the Great Patriotic War of 1941-1945.

The article briefly describes the establishment, functioning and activities in selected periods of the national history of the Gorky House of Scientists - the first House of Scientists in our country. Russian scientific and pedagogical community celebrated its centenary at the beginning of this year. The authors emphasize the social function of the House of Scientists activities. Their significance historically had been most pronounced during the hardest times for our country.
The paper determines the role of the House of Scientists as a center for interprofessional communication and reproduction of researchers. In 1932 the House of Scientists was named after M. Gorky. In 1937 it was placed under the USSR Academy of Sciences. In the same period, scientific sections began to form, scientific conferences were held, and cultural and educational work intensified. The features of functioning of the House of Scientists in the pre-war period, during the Great Patriotic War and in the first arduous post-war years are highlighted.
The authors focus on activities of the Gorky House of Scientists starting from the second half of the 1950s when its function as a center for interdisciplinary scientific communication became more and more pronounced. A fundamental step in this direction was the creation in 1956 of the cybernetics section at the House of Scientists, the leadership of which was initially assumed by the Nobel laureate L.V. Kantorovich (1912-1986). Then, for more than thirty years, the work of the section was led by Professor L.P. Kraizmer (1912-2002). Shortly before the section of cybernetics, in 1953-1954, the section of economics and statistics at the House of Scientists was created (currently - the section of socio-economic problems and statistics). Milestones for the section of socio-economic problems and statistics of the Gorky House of Scientists are outlined in the article by I.I. Eliseeva and A.L. Dmitriev, published in the journal “Voprosy statistiki” (2018, No. 8, pp. 52-65).