Investigation of the Relations Between Foreign Trade and Characteristics of Environmental Quality: Existing Approaches and Approbation of Gravity Modeli

The purpose of this study is for the author to summarize approaches and methods for assessing availability, identifying forms and types of relations between characteristics of environmental quality and international trade, and also to test the gravity theory of trade as such a method (on the example of the Republic of Belarus).The author has investigated modern economic works devoted to the study of the influence of trade liberalization on environmental pollution, the pollution haven hypothesis, the environmental Kuznets curve, the Porter hypothesis, etc., as well as the studies aimed at confirming or refuting these hypotheses, has systematized modern approaches to assessing the relations between trade and environmental indicators.Based on the panel data for the period from 1995 to 2019, the author has constructed the gravity models of trade (separately for export and import) of the Republic of Belarus with the EAEU partner countries and neighboring countries (Lithuania, Latvia, Poland, Ukraine), taking into account the environmental impact (the carbon dioxide emissions as the proxy variable of pollution). The simulation results have confirmed the theoretical provisions of the gravity theory. In addition, a significant effect of an increase in carbon dioxide emissions of countries – trade partners of the Republic of Belarus on its imports has been revealed.

Measuring the ICT Sector in the Digital Economy

The article addresses the problem of measuring the Information and Communication Technology (ICT) sector and its relationship to the digital economy as defined in the OECD «Guidelines for Supply-Use Tables for the Digital Economy». Analysis of various concepts of the digital economy shows that the ICT sector is its key element. It is stressed that, in line with the OECD recommendations, the measurement of the digital economy should be based on the SNA satellite account, the core element of which are the Digital Supply-Use Tables (Digital SUTs). This approach enables to reflect most fully within a single statistical model integration of all phases of digital products (goods and services) circulation in the national economy.It is noted that the construction of ICT Supply-Use Tables (SUTs) is a critical self-contained task, as it provides a measurement framework for both digital (regardless of the model to be adopted) and (more broadly) information economy.It is stressed that the ability to capture the use of ICT products as well as the cost of their production depends significantly on the identification and valuation of digital products and industries in the Digital SUTs. The identification of such industries is now a major challenge because of the lack of separate activities in the existing industrial classifications that are characteristic for their constituent units.The article concludes with a presentation of the pilot estimates of ICT Sector SUTs core indicators obtained by the authors at the Economic Statistics Centre of Excellence, HSE University. The contribution of the sector to the GDP of the Russian Federation is analysed and its inter-sectoral linkages, both on the demand and supply side, are assessed. It is concluded that the full implementation of the Digital SUTs depends on the inclusion in the new International Standard Industrial Classification (ISIC) the additions necessary to identify and evaluate digital products and industries.

Features of the Formation of Technological Expectations in Russia: Analysis of the Results of Business Tendency Surveys of Digital Transformation of Manufacturing Enterprises

The purpose of the article is to analyze the technological expectations of managers of Russian enterprises from the manufacturing industry in the face of changes in the external economic environment. Firstly, the authors have calculated a specially developed «index of fulfillment» of technological expectations, reflecting the ratio of the expectations of the introduction of digital technologies formed in the previous period and an increase in the real level of implementation. Secondly, using regression analysis, the authors investigated the mechanisms of the formation of technological expectations of managers in various conditions: non-crisis 2018, pre-crisis 2019, and crisis 2020. The influence of the three mechanisms was tested in intertemporal context: the «inertial» one, which presupposes the preservation of the expectations formed in the past in the current period; «adaptive» which involves adjusting expectations in accordance with the current dynamics of technology implementation; «predictive» which implies the connection of expectations with the future level of implementation.The basis for empirical calculations was the data of annual business tendency surveys of digital activity of Russian manufacturing enterprises for 2018–2020. The aggregate sample of surveyed enterprises for three years included more than 3000 enterprises from 23 manufacturing industries. The paper studied patterns of implementation of 19 digital technologies, most of which, according to specialists, belong to Industry 4.0.The results obtained indicate that technological expectations are characterized by great heterogeneity in terms of feasibility. Regression analysis showed that all three identified mechanisms can play a role, but their influence varies. In particular, when a crisis occurs, the adaptive mechanism plays a key role, and the inertial mechanism becomes irrelevant.The results of this study indicate that Russia is characterized by the initial and transitional nature of digital transformation in the manufacturing industry, with technological development achieved through «breakthroughs» rather than a steady process of modernization. The main conclusion of the work is that external uncertainty greatly affects the evolution of technological expectations, destroying their continuity from previous plans and negatively affecting the predictive capabilities.

Reliable Assessment of Inflation as an Objective Necessity

The article is devoted to laying out methodological foundations for assessing the level of inflation in modern Russia. It justifies using aggregate (integral) indices to characterize price processes and determine strategic development priorities.The use of inflation indicators used in the international practice in Russia does not provide the necessary level of reliability of information about the ongoing inflationary processes in various sectors of the national economy. It does not allow us to objectively assess the current state of socio-economic development to timely capture and account for changes in the trends of strategic development. As a result, the quality of analytical work, first and foremost carried out by real sector development institutions, is reduced, which affects the effectiveness of decisions made by economic entities and public administration bodies.The authors argue that the aggregate inflation index shows a higher degree of variability in the dynamics of inflationary processes than the consumer price index since it accounts for changes in the most significant sectors of the economy, the social sphere and the financial sector.The article proposes an improved method for constructing an aggregate inflation index based on mathematical and statistical methods. It is shown that the use of an aggregated inflation index increases the objectivity of the assessment of economic growth and social progress, which makes it possible to more quickly predict the dynamics of costs and results with a sufficiently high degree of forecast accuracy.The need for regular adjustment of the composition of private indicators taken into account in the formation of the aggregate inflation index is justified by including new, more relevant indicators and excluding those that have lost their relevance.Results of the study are the conclusions obtained by analyzing the dynamic series of aggregate and partial inflation indices formed on the basis of the methodology proposed by the authors.

Financial Behavior of the Russian Population: Regional Differences

The introductory part of the article specifies the aim and objectives of the study, reflecting some of the important outcomes of the interregional differentiation in the financial behavior of the population of individual Russian territories (in more detail – regions of the Far Eastern Federal District, FEFD).The main section of the article identifies interregional differences in the financial behavior of the population of the considered regions of the country, including the FEFD territories, based on statistical methodology and using official statistics. The authors conducted a comparative interregional analysis of the structure of consumer spending, average per capita deposits, and public debt on loans granted by credit institutions for the period 2018–2020. Specific statistics show that the FEFD regions are experiencing a negative trend of accelerating the debt of the population to credit institutions.The article concludes with outcomes of an interregional comparative analysis of the considered characteristics, reflecting the emerging negative trends in the financial behavior of the population, showing that parts of the eastern part of the country lag markedly behind the general trend in social and economic development.

Assessing the Impact of Country Risk on the Investment Attractiveness of Russian Companies

The ability to attract foreign direct investment (FDI) is a critical success factor for the development of any participant in the local market. One of the indicators that characterize the investment attractiveness is the economic value added (EVA). It reflects the market assessment of the company's profit potential. Some EVA assessment methodologies include the country risk assessment – a factor that is beyond control. This study analyzes the impact of this indicator on the investment attractiveness of an organization. The authors estimated the economic value added for some of the largest Russian companies using methodologies that take into account the country's risk level, as well as those methodologies that do not take it into account. The calculations used adjustments for EVA in line with specific features of Russian accounting. As a result, it was revealed that, regardless of industry affiliation, the investment attractiveness of Russian organizations decreases when the country's risk factor is included in its assessment.The article justifies the relevance of the developed approach to the assessment of investment attractiveness of companies based on country risk level as a factor that impacts the ability of organizations to generate profit, making it possible to detect hidden management problems. According to the authors, the application of this approach not only contributes to the solution of long-term and medium-term tasks of business development (for example, the creation of its infrastructure) but also greatly facilitates the entry of organizations into international markets.One of the authors' conclusions of the study is that using the methodological tools developed by them for analytical purposes requires improving the management of the investment attractiveness of an organization and, consequently, its objective assessment. The structure of economic value added can serve as a basis for making management decisions related to increasing investment attractiveness. According to the authors, the provisions formulated in the article can serve as a methodological guide for organizing business valuation based on the EVA in the Russian context. Results of the study can be of interest to managers, current owners of companies, and potential investors.

On the Origin and Development of the System of National Accounts

The article covers milestones of the system of national accounts (SNA) development. In particular, it is noted that the SNA was developed in response to the need of governments of the major market economies in macroeconomic statistics to guide decision-making for combatting the effects of the Great Economic Depression of 1929–1933. The authors address the SNA evolution in a context of the development of concepts, definitions, and classifications, furnishing the basis for a system of interrelated and mutually agreed measures of economic development at the macro level.Development of the SNA theory and methodology was closely linked with real change in a global economy, reflected the emergence of new forms of organization of economic process, new methods of financing investments, the growing role of foreign investments, globalization.The authors note a valuable contribution of a galaxy of eminent economists of the last century to the SNA theory and methodology elaboration. The article discusses at some length the role of international organizations in the development of theoretical and methodological foundations of the SNA. After the Second World War, these organizations released several critical documents with recommendations on the SNA compilation, recognized as international standards. The authors analyze the current international standard – the SNA 2008. In particular, the new treatment of expenditures on research and development and weapons systems. This treatment introduces a very noticeable adjustment in understanding important structural characteristics of the modern economy in many countries.The final part of the article considers issues of developing the SNA in national statistics, previously focused on the balance of the national economy (BNH). There are specific features of the transition from the world’s first developed system of interrelated macroeconomic indicators, the BNH, to the international standard, the SNA, adapted to modern realities of unctioning of market economy in Russia.

Cluster Analysis of Russian Universities Based on the Dynamics of Their Performance Indicators

The article presents the results of a study, the aim of which is to investigate the dynamics of the development of Russian higher education institutions based on an analysis of their performance indicators. The sample includes 535 universities from 80 constituent entities of the Russian Federation. It presents the results of the clustering of universities on the basis of changes in indicators of six variables characterizing the key areas of activity of universities for the period from 2013/2014 to 2017/2018 academic years. The characteristics of each cluster are described, an inter-cluster comparison of quantitative indicators of the activities of universities is presented.As a result of the calculations of the average annual growth rates of six key indicators characterizing the activities of universities, fve clusters were identifed that differ in their development trajectories. Thus, the universities that belong to Cluster 1 over a fve-year period retained or improved their positions in the main areas of educational activity and managed to maintain income growth at an average level.However, their indicators in such areas as international and research activities, as well as infrastructure development (provision of educational and laboratory facilities) have decreased. In universities from clusters 2 and 3, all performance indicators changed in a fairly balanced way. At the same time, the indicator of an increase in the internationalization of the students’ body was signifcantly higher in Cluster 2, while educational organizations from Cluster 3 showed a signifcant increase in the publication activity of academic staff.The results of the activities of universities in Cluster 4 were positive in all considered areas. This cluster had the highest average annual growth rates in the average Unifed State Exam (USE) score and publication activity of the academic staff. Educational organizations from Cluster 5, on the one hand, achieved the best results in attracting foreign students, increasing the proftability of their activities and the provision of teaching and laboratory facilities but, on the other hand, their average annual growth rate of the average USE score has signifcantly decreased.The study represents one of the frst attempts to cluster Russian universities based on the analysis of changes in their performance indicators. Previous studies on the clustering of universities were mainly based on the analysis of one-time indicators. The approach proposed by the author makes it possible to compare indicators of the dynamics of development of higher educational institutions of different size and scope. Further research in this area could be aimed at analyzing a larger number of performance indicators of universities and studying in detail their strategies for a deeper understanding of the reasons for the differences in their effectiveness.

The Application of Cointegration Method for Structural Data in the Estate Market Analysis

The article touches upon the topical issues of the residential real estate market, which are proposed to be solved by means of time series cointegration. The study aims to assess the structure of the housing market by types of apartments using price dynamics per one square meter of apartments' total area. The objectives of the study are to develop a methodology of determination of time series cointegration for the data with structural relationships; to analyze the average prices for the types of apartments on the primary and secondary housing market; to study the housing market in the Russian Federation by quarterly data of state statistics for the period 2000–2020 based on the developed methodology.The results of the research showed that the prices at the primary and secondary housing market by types of apartments do not always represent an integrated process of the frst order and cannot be used for building a co-integration equation. This necessitated additional analysis and, as a consequence, the correction of the time period. It was proposed to ensure stationarity of linear combination of nonstationary data corresponding to the integrated process of the frst order by using the generalized least squares method (GLS). The sum of the elements of the cointegrating vector obtained this way tends to unity, and the elements themselves are estimates of the relative indi cators of the structure by types of apartments on the primary and secondary housing markets respectively. Thus, the suggested methodology allows estimating, on average, the share of the sold apartments of each type in the period under consideration, both in the regional context and in the country as a whole.The proposed methodology can be used for the estimation of relative indicators of the structure according to temporal data in different applications.

Structural Shifts in the Economy of the Russian Federation and Its Import Intensity in 2014–2019: Analysis of Macroeconomic Statistics.

The introductory part of the article formulates its objective – to characterize development conditions in Russia and main structural changes in the Russian economy (according to 2014–2019 data) from the standpoint of their compliance with the tasks of increasing the stability and quality of the country's economic growth during the transition of the world system to a new technological order. Аccording to the authors, this period is of particular interest in assessing and studying the experience associated with structural transformation in a highly unfavorable external condition amid tight monetary policy and restrictive income policy.The article sequentially addresses certain aspects of the structural transformation of the Russian economy. The authors, relying on macroeconomic statistics, assess shifts in production and use of products, investment, import intensity, the balance of payments, and international investment position, considering external and internal conditions.The paper focuses on analyzing the proportions of the economy according to the data of the Rosstat input-output tables (IOTs). The article provides estimates of structural changes in the dependence of the economy and its segments on types of imports, signifcant changes in the direction of the use of fnal products, including considering the dynamics of changes in the total input of intermediate imports. For the frst time, the characteristics of the concentration of gross value added (GVA) and gross domestic product (GDP) by areas of fnal demand are given. A methodological approach is proposed for monitoring shifts in import consumption by compiling annual summary tables with a minimum set of data obtained during the analytical processing of IOT information. Based on the results of testing this approach on data for 2016 and 2018, the authors rated cost product balances by the share of imports in the resources of products. Conclusions were drawn about the change in the import intensity of the economy for the selected types of products, the import intensity of Russian industries, and shifts in the distribution structure of types of imported products. The article formulates proposals for the development of measures necessary to consolidate and expand positive results of this stage in the development of the Russian economy and statistical support of macroeconomic analysis.