The return of the economy to normal development conditions in the post-coronavirus period implies not only the understanding of the new content and the relationship between quality and growth dynamics but also the advancement of methods for analyzing and forecasting economic dynamics and growth factors at macroeconomic, inter-sectoral and sectoral levels. The article examines the possibilities of using two main research tools for these purposes: inter-industry models based on the Input-Output tables, and macroeconomic and industry factor models.
The authors not only cover a long history of the application of classical models of this type but also demonstrate new directions of their use in solving specific tasks of analysis and forecasting in a market economy based on the analysis of a modern system of «Input-Output» tables and development of the investment and fixed assets block model. In addition, the development of macroeconomic analysis methods that can be implemented through the sharing of inter-industry and factor models is highlighted. Based on factor models evaluation, the authors identify unique characteristics of individual periods of development of the Russian economy in the first 20 years of this century, the evolution of dynamic trends and reveal the role of main economic growth factors, as well as anticipated limitations of these factors in the long-term period. Using the research findings and taking into account requirements of the new wave of technology, the conclusion is made about the crucial role of the growing investments in innovation and infrastructural sectors of the economy and enhancing the efficiency of investment activities, but this applies even more to improving the quality of human capital. Formalized and non-formalized aspects of its assessment are noted. The latter address the problems of training and nurturing highly-skilled specialists (doers), but above all of unlocking the creative potential of the young generation, which have yet to create a new technological and social structure. The article also proposes the solution for several instrumental and methodological issues related to the development and use of models of this type. It is shown that sharing of cross-sectoral models, macroeconomic and sectoral factor functions allow for a more comprehensive approach to the analysis and forecasting of the economy, it links growth factors to production, and reflects the direct and inverse relationship between demand and supply. Directions for modeling of the necessary fixed capital investments coupled with production dynamics, support of the production facilities and carry-over (incomplete) construction, which, are according to the authors, an important step towards building a dynamic cross-industry balance.

The article proposes a new set of composite indicators-predictors in business tendency surveys, which allow identifying early information signals of a cyclical nature in the economic behavior of business agents. The main criterion for the efficiency of such indicators is their sensitivity to a cyclical pattern and changes in the dynamics of statistical referents. Property such as a statistically significant lead in time series or earlier publication allows them to be combined into indicators of early response. The composite Business Activity Indicator (BAI) in the basic sectors of the Russian economy is calculated by the authors for the first time based on the results of regular (monthly and quarterly) business surveys of Rosstat for 1998–2020 with a large-scale coverage of sampling units. In 2020, the number of survey respondents averaged about 20,000 organizations of all sizes. The index reflects the «common» profile in the dynamics of short-term fluctuations of the key parameters of the economic environment, which consists of the «balances of opinions» of respondents to the questions unified for all sectoral surveys and connected with the reference quantitative statistics with cross-correlation coefficients that are statistically significantly different from zero, with a lead at least one quarter. This is its main difference from the well-known indices of economic sentiment and entrepreneurial confidence. The main components of the BAI are the new composite indices of real demand, current output, real employment, total profits and economic situation. They aggregate the relevant «order» statistics for the basic sectors of the national economy, including the main kinds of industrial activities, retail trade, construction, and services.
The article provides a methodological substantiation and an extended procedure for identifying the BAI components; their composition is formed for the entire set of retrospective results of business tendency monitoring in Russia. A new Aggregate Economic Vulnerability Indicator with a counterdirectional profile and varying degrees of symmetry of its dynamics relative to the short-term movement of the BAI is being introduced as the main limitation of business activity. Proactive monitoring of emerging vulnerabilities in the business environment is necessary to warn their large-scale accumulation, prevent the risks of economic downturns and ensure the highest possible macroeconomic stability. This integrated approach makes it possible to determine the novelty of the proposed measurements of short-term cyclical fluctuations in economic development.

The article presents results of analysis of the predictive potential of short-term forecast estimates of employment level in the small business segment by four sectors of the Russian economy: manufacturing, construction, wholesale and retail trade.
From the authors’ point of view, one of the promising sources of data for such estimates can be found in market observations of entrepreneurial activity, which now are a common source of economic information in national as well as international practice. These surveys play an important role in measuring the dynamics of employment in countries and industries, being a supplementary statistical tool.
The objective of the work was to prove the existence of a stable statistically significant relationship between the predicted estimates of employment based on business (market) surveys and the dynamics of the corresponding statistical macro-aggregates in various sectors, and applicability of predictive models of employment change based on results of business (market) surveys.
The novelty of the presented results (authors’ contribution) resides in the fact that for the first time, using an expanded sample (over 14 thousand respondents), were studied the possibilities of predicting labour market indicators in small businesses based on leading data from business surveys, examining separately retail trade, wholesale trade, construction, and manufacturing. According to the results obtained based on the Granger causality and pseudo-out-of-sample analysis, in all the industries under consideration, entrepreneurial assessments and expectations are effective predictive indicators for forecasting employment dynamics in the short term (two to four months) and identifying turning points in employment growth in the small business segment. The most sensitive predictive estimates were found in the retail and wholesale sectors, with the best results obtained for wholesale trade. For this reason, the authors recommend using the employment expectations indicator primarily in these sectors to monitor the level of employment and unemployment.

The article scrutinizes one of the most acute problems in Russian society – the continued high level of separations among first unions.
According to the official statistics data, Russia has consistently held a leading position in terms of divorce rates among European countries.
Recent estimates of period total divorce rates suggest that 30–40% of marriages contracted in the 1970-1980s and 50–60% of marriages contracted in the last two decades have a chance of being dissolved.
The authors use materials from the panel part of the sample survey «Parents and children, men and women in the family and society» to examine the stability of first unions formed in 1945–2010 – either direct marriage, marriage after cohabitation or cohabitation in partnership cohorts. The results suggest an increase in the proportion of dissolved marriages from 14% in the marital cohorts of 1945–1954 to 30% in marital cohorts of 1980–1989. In these cohorts, «direct» marriages were more stable than marriages, which followed cohabitations. However, it is not so obvious for marriages preceded by cohabitations in the 1990s.
Authors conclude that the average duration of a dissolved marriage and the average age of women at the time of the dissolution of the marriage have decreased. Cohabitation remains the least stable form of union with an average duration of 4–5 years. Childless unions break up 2 times more often both among marriages and cohabitations. There has been also a decrease in the average number of children in all types of broken unions with children.
Based on results formulated at the final part of the article the authors suggest that the «direct» marriage without prior cohabitation become a less attractive form of union that might positively affect the stability of Russian marriages by reducing the probability of divorce due to such grounds of divorce as incompatibility in characters, views and beliefs, especially in the initial years of joint life.

The article substantiates the relevance of the issues in question, which have been exacerbated by the coronavirus pandemic and provides a brief overview of the scientific and practical sources, as well as a description of current research related to both traditional methods of statistical accounting of tourist travel and methods based on the use of big data sources.
The review shows current methodology as well as different suggestions, encountered in various research studies, on how to assess inbound, outbound and domestic travel. The evolution of Rosstat’s approaches to accounting for the number of inbound and outbound trips has been analyzed, and certain adjustments to existing methods relating to the accounting of organized and unorganized trips have been proposed.
The results of calculations illustrating the predominance of unorganized tourism when making inbound and outbound trips are presented. In general, it is concluded that the most difficult is the comprehensive monitoring of internal travel. Three possible approaches to the accounting of trips are shown. The option of using the approach to accounting for domestic tourist travel based on monitoring of passenger traffic, which is consistent with international recommendations and the existing classification group «Tourism» in our country, is proposed. In addition, the option of accounting for domestic regional tourist trips based on official forms of reporting is shown.
It is the author’s opinion that the implementation of the reasoned proposals should serve to improve the reliability and objectivity of statistics on tourist travel. This, in turn, will create the conditions for improving measures to support the tourism sector of the economy, particularly necessary in the economic crisis triggered by the coronavirus pandemic.

In the current context of recovery growth in Russia, the urgent task of identifying factors of growth of labor productivity can be solved using econometric methods. Preliminary examination of interregional comparative analysis of dynamics of this crucial economic efficiency index, in the author’s opinion, showed low information content of this approach due to the presence of a low base effect. The author recommends a more realistic approach to the interregional comparative analysis of the labor productivity dynamics and its growth factors on the basisof econometric panel data models.
It was revealed that for the period 2010–2018, the growth of labor productivity in the regions of the Russian Federation strongly correlated with dynamic characteristics of industrial production, real wages and physical volume of investments in fixed assets, growth intensity in the share of added value of high-tech and knowledge-intensive industries in GRP. It has been empirically proven that the growth of labor productivity in the regions in the considered interval correlates with a decrease in the number of employees. In addition, an increase in labor productivity is typical for constituent entities of the Russian Federation with high rates of industrial production.
The influence of the structure of employed in the economy on the level of education on the growth of labor productivity has not been established, which may indicate the presence of inefficient jobs. Also, the hypothesis that the export-oriented regions of the Russian Federation are highly productive has not been confirmed.
In conclusion, taking into account the results of modeling, the author formulated recommendations adjusting focal points of structural changes in the economy, which could boost labor productivity growth.

In the article, the authors express their opinion on the outcomes of social and economic development of Russia in 2020 and give a forecast of expected results for 2021 and 2022. The state and possible directions for overcoming stagnation are considered, primarily by closing the technology gap in production and ensuring the growth of labor productivity, business, investment and consumer activity, increasing the efficiency of capital investments as key factors in the recovery of the real sector and the knowledge economy, including industrial production, agriculture, capital construction.
The drawbacks of the current management system are noted, and measures to overcome the structural crisis are proposed. The need for changing the state socio-economic policy is substantiated. Its main goal should be to ensure the health of the nation.
The authors compare trends in the Russian and world economies by main development indicators, such as gross domestic product, industrial production, investments, foreign trade.
The article examines the shortcomings of the current state financial policy, which should become an instrument of financial support for sustainable socio-economic development and countering external and internal risks and threats. The problems of execution of the federal budget for 2020 are analyzed. Using case examples, the authors prove the necessity for priority use of financial resources of the «rainy-day fund» to accelerate the development of sectors of the national economy.
Given the slowdown in global economic growth in 2020 and problems associated with its full recovery in 2021, the expected expansion of trade wars and sanctions lead to a conclusion that there is a growing negative trend in the Russian economy as well with the potential of stagnation escalating into recession.

The article covers the results of the author’s study on improving the methodology for measuring (estimating) the impact of foreign trade on the nature of reproduction processes in the Russian economy. The parameters and nature of domestic economic development are largely determined by its reproductive model based on raw material exports. The shift in external conditions (from very positive to severe negative) was, according to the author, one of the main factors in the transition from the spectacular growth during «boom» years from 1999 to 2008, and stagnation of the «lost decade» from 2010 to 2019.
The article reviews methodological provisions of the international statistical standard – 2008 SNA for calculating aggregates of real income for the total economy, profit (or loss) from foreign economic activity with emphasis on the need to take into account changes in terms of foreign trade in recent Russian history, before the coronavirus pandemic of 2020–2021. Various approaches to calculating macro-indicators of foreign trade activity – trading gains and losses and real income for the total economy are analyzed within the concept of a system of national accounting. In this regard, the article analyzes indicators under consideration in the context of terms-of-trade changes and highlights the relationship between GDP volume (at comparable prices) and real income characteristics in the macroeconomic system.
To ascertain the evolution of characteristics of the impact of the export-raw commodity orientation of Russian foreign trade on the reproduction in general, the author within the 20-year period under consideration selected several separate periods: 1995–1998 – transformational recession, 1999–2008 – uniquely favorable conditions, 2009–2014 – recovery from the global crisis, 2015–2019 – transition to macroeconomic stability. The impact of foreign trade on the national economy was analyzed. There is a conclusion about the additional analytical capacity of researchers dealing with problems of reproduction amidst globalization using the following national accounts indicators: profit (loss) from foreign trade and real income aggregates - in a rapidly changing external economic environment.

The article presents results of a study on influence of population dynamics, regional characteristics and the type structure of income on consumption. The ability to investigate spatial dependencies and territorial effects over time was made possible by autoregression spatial models built on panel data. The article describes features of such models, sequence of calculations, and also presents modified tests to justify the choice of the model specification.
Calculations were made using data from 83 constituent entities of the Russian Federation (cross-sectional observations) for 2010–2019 (10 time periods). The analysis showed that both population income and retail turnover, which largely determine the level and structure of population consumption, have spatial dependencies. The built spatial error model with fixed effects showed a positive influence on population consumption in the neighboring territories. The model also confirmed previously identified relationships: the positive impact of average per capita income and the negative impact of the Gini index on consumption. The built model with fixed effects allowed to isolate the individual effects of the territories, visualized using cartogram. On the basis of these assessments, several groups of territories with common properties and characteristics have been identified.
Unlike previously built models, the authors’ spatial error autoregression model, built on panel data, took into account both the geographical heterogeneity and spatial dependence of average per capita income and retail turnover, expanding the existing understanding of the relationship between consumption and income. This, in turn, enables management decisions that take into account previously undetected features and enhance their validity.