The paper addresses methodological and practical issues of statistical evaluation of the digital economy in macroeconomic calculations. The UN Statistical Commission has determined the statistical description of digitalisation processes as one of the priorities of the SNA research programme.

The author examines the problems and structure of Digital Economy Satellite Account (DESA) proposed by OECD as a complex tool for measuring digitalisation processes. Compiling this account will enable statisticians to evaluate all measurable phenomena in a digital economy and expand the production boundaries by including free digital services into the evaluation.

Compilers of the new SNA satellite account now focus on Digital Supply and Use Tables (DSUT) that play the role of core structure for the future DESA. In the process, the traditional SUT structure is revised by including new groups of specific products and extracting digital components of several products of CPA classification. Moreover, developers add new industries that form by reclassifying producer units en­gaged in digital production.

The author explores the issue of measuring «digital» value added and outlines approaches to solving it used, for example, by the US Bureau of Economic Analysis. He also gives a summary of the relevant methodological challenges affecting DESA compilation.

Special attention in the paper is paid to the problem of valuation of data (information) which is not covered by the existing 2008 SNA methodology. The author proposes to evaluate data as a non-produced asset, using the Net Present Value (NPV) approach. According to it the value of information (non-produced asset) at a specific moment is equal to the difference between the sum of discounted future incomes of the organisation and the value of its fixed capital. Such an approach could be applied to the valuation of data used as a principal subject of activity by organisations producing digital products.

The paper also presents various aspects of statistical evaluation of free digital products.

It is the author’s opinion that approaches to statistical evaluation presented in this article could serve as a basis for creating the system of such measures in the Russian Federation.

The article is prepared based on the results of theoretical studies conducted by the authors in the field of actuarial calculations, the improvement of which is one of the development directions for statistical science.

In modern economic conditions, the assessment of risks inherent in economic entities in all spheres of activity and leading to significant losses, such as credit, operational risk, liquidity risk, and so forth is of particular importance. Quantitative assessment of the level of risks is the subject of actuarial calculations. However, the existing apparatus of actuarial science is mainly focused on solving specific issues facing the insurance industry (including pension insurance) and is not adapted to assess the level of risk.

The article presents the key positions of the author’s theory of actuarial calculations, which offers a generalized approach to solving actuarial problems in various types of economic activities using a variety of information about the risk. The basic idea of the theory is that any result of actuarial calculations can be expressed in terms of quantiles of the future net loss associated with the realization of risk.

The estimation of each quantile can be considered as a special case of evaluation of unobserved economic values, such as cost, projected profit, and so forth. The problem of estimating these values lies with the multivariance of the original data and methods, as a result of which different specialists often receive significantly divergent estimates.

For this, the author proposed to use the methodology of evaluation, which consists in obtaining the median of all single estimates that can be obtained from representative samples of possible scenarios, evaluation models and values of the original data. This methodology can be used to estimate the quantiles of the future loss, and the complexity of the original data involves the use of numerical methods, in particular, the Monte Carlo method.

The authors tested research tools on the example of solving the problem of quantitative characteristic of credit risk. They also constructed and estimated the mathematical and statistical model of loss from the default of the borrower, and proved the possibility of sufficient repeatability and reproducibility of results. The data of state statistics, financial statements of credit institutions, model estimates served as initial data.

This article addresses the potential of mathematical and statistical modelling the change point detection in economic systems on the example of UC «RUSAL». Change point prediction of stable or quasi-stable periods of economic systems is necessary for the operational changing of a strategy, tactics and control of the considered economic system. It solves one of the robust control problems, the purpose of which is the synthesis of the regulator that can provide the preservation of output variables of the system within the robust limit for all types of membership functions and the uncertainty of the input data.

The developed algorithm is based on the study of the behavior of residuals of regression models by the observed series of the dynamics of some exponent (as a benchmark was chosen the price of ordinary share). This algorithm is applicable for small volume samples, which, as a rule, are the series of dynamics of exponents of economic systems and also, in the study of non-Gaussian observational models.

The author explores the nature of criticism levelled against official Russian statistics. The article reveals the objective reasons behind specific problems associated with collecting primary data. It also demonstrates that cheap political chicanery of some members of the opposition or individual members of the scientific community who bash to attract attention to themselves and with that detriment of the objective need to understand the questions that the general public has for authority.

Another aspect of this issue is that often unsubstantiated and unsupported statements referring to Rosstat’s almost deliberate falsifications and misstatements of the real situation deflect attention away from actual problems of statistics’ independence, its organizational and financial support from the state. The author concludes that any allegations against the current system of state statistics severely dent the credibility of the government, that with its own hands preordain financial capacity of statistics and its limits of independence. Therefore, the way authority treat statistics serves as an indicator of its maturity, whereas statistics with its assessments and evaluations should come as close to the truth no matter how unpleasant. So, the heading is a refrain of the whole paper: statistics as amarkof maturity of the authority.

In this article, the author outlines results of the 2016 Russian Census of Agriculture (VSHP-2016) and goes in detail reviewing questions related to the micro censuses of agriculture that in line with the Federal Law № 411-FZ from 1 December 2014 are conducted five years after a decennial agricultural census. This type of sample federal statistical survey of individual agricultural census items will require at least 30 percent of them to be selected.

The article explores various ways to solve technical issues of conducting micro census. There is an alternative approach to conducting an agricultural micro census that focuses not on selecting individual census items but rather on municipal districts (urban districts), in which it is recommended to conduct a complete survey. Results of such sufficiently informative and less costly survey can, in the author’s opinion, without large sampling errors help identify new trends and structural shifts in the development of agriculture in the constituent entities of theRussian Federation, including their municipal units. It also allows for getting information on the size, composition and dynamics of its resources amidst the transition of all categories of farms to market relations and implementation of state target programs.

The modern Digital Universe changes and expands at a speed that every two years double the amount of data. It leads to a situation when huge accumulated flows of information can no longer be covered by traditional scientific search and built into a relevant scientific research framework. The authors argue that there is a need for using modern statistics and scientometric application packages for solving research tasks in the primary trends of the information economy. The article presents a comparative analysis of various scientometric programs and describes a new approach to identifying and visualizing patterns and transient regularities in the scientific literature on the basis of a study of global publication flows in the last 25 years in the subject area of «labour economics» represented in the Web of Science.

The authors conceptualize and visualize scientific domain of «labour economics» within the framework of the timing diagram of the evolution of research fronts. They introduce the search algorithm for active research fronts in the global information flow using CiteSpace V.0 and highlight the most critical trends and principal points of research clusters for the past decade on labour economics and its core studies. The paper determines most perspective citation spikes that could potentially become the center of new scientific knowledge in this area and outlines opportunities for future research.

In 2018 CIS-Stat surveyed national statistical offices of all member states of the Commonwealth regarding the list of topics they plan to include in the 2020 census programmes. This material is a result of thorough analysis of the information presented along with questionnaires from 2000 and 2010 census round. The article covers core census topics that the CIS member-states plan to include in their census programmes of the 2020 round. Population census topics are designed to maintain continuity with the previous censuses, to meet national information needs and are consistent with international recommendations. Much of the national population census programmes preserve the traditional structure. However, every round brings own features given the information needs of every state of the Commonwealth.

Pilot population censuses are conducted in order to test methodological and technical solutions. Pilot censuses have currently been completed inBelarus(in 2017),Azerbaijan,Kazakhstan,RussiaandTajikistan(in 2018). This material presents general characteristics of testing of materials and documents included in the core headings of the census programme. All of them have commonalities as well as own features that serve the information needs of a country. The authors explore the following sections of census programme: “Population to be enumerated, household and family characteristics”, “Demographic and ethno-cultural characteristics”, “Marital status and fertility”, “Geographical and migration characteristics”, “Characteristics of persons, temporarily present in the country”, “Educational and economic characteristics”, “Other population and household characteristics”.

Population censuses in the CIS countries continue to be one of the pillars of data collection on the number and socio-demographic, economic and ethno-cultural characteristics of the population of a country; at the same time, some topics - educational attainment, marital status, language and ethnicity - can only be investigated in a census of population.

The 2020 census round in the CIS countries stands out as having agreed upon methodology for socio-demographic characteristics, particularly information on migration and work force. Harmonized methodology will allow national statistical offices to more precisely determine the flows and volume of international migration, along with the total size of the Commonwealth labour market amidst the fast approaching census date.

This article is devoted to the commemoration of the 100th anniversary of the Journal «Voprosy statistiki». In it, the author shares her opinion on the evolution of the journal for the past several decades commenting further on the period from the second half of 1980th. It was Perestroika - the democratization of society, development of the policy of open discussion («glasnost») and transition to the market economy - that led to reforms in the state statistics. This period marked a significant shift in the journal’s evolution. It started accepting articles introducing the readers to new, original approaches to various research fields in statistical science. They covered questions related to the economic reform, development of new methodological approaches aimed at reforming the system of statistical indicators and improving methods of statistical observation; as well as introducing into statistical practice the improved system of the national accounts: 2008 SNA instead of 1993 SNA.

The author not only reminisces about Russian scientists and educators in statistics but also characterizes them from different perspectives as professionals and human beings; she addresses their role in establishing the school for training statistical personnel, that is relevant to this day. The article touches upon the question of increasing statistical literacy that today is an integral part of professional training of specialists in science and education, production, business, and other areas.