Macroeconomic Dynamics of the Total Factor Productivity of the Russian Economy

The growth rate of Russia’s total productivity has been slowing down significantly since 2008. The majority of relevant publications either describe an economic methodology or specifically focus on labour productivity. However, economic growth rates, as well as community welfare, largely depend on total factor productivity. The paper aims to determine the reasons for the slowdown in the growth of total factor productivity after 2008. This negative dynamics was assessed using a macroeconomic econometric model and estimates for Russian regions and types of economic activity. Elasticity of dependent variables was calculated based on econometric equations as well as multipliers of exogenous variables presented in the model. Ordinary and rank correlations between the variables were also examined. The calculations revealed that the stagnation of total factor productivity was caused by the misallocation of resources across industries and regions, de crease in aggregate demand, increase in capital goods prices (primarily due to rouble devaluation) and a slowdown in digital economy development. In turn, these trends were influenced by a decline in public investment and export prices, as well as a slowdown in population growth and liquidity. Simultaneously, growth of the world economy contributed to the demand for Russian export goods, preventing a decrease in productivity. The findings can be used for forecasting Russian economic trends and developing relevant policy measures. Further research will examine the role of human capital, energy intensity, climate and institutional factors in increasing the total productivity.

Assessment of Migration Policy Measures Implemented in the Russian Far East

The present paper analyses migration policy measures implemented in the Russian Far East, namely, State Programme to Assist the Voluntary Resettlement of Compatriots Living Abroad to the Russian Federation, the Far-Eastern Hectare Programme, establishment of Priority Development Areas (PDAs) and territories with a special regime of economic activity. The synthetic control method was applied to quantitatively assess how the adopted measures affect the migration outflow from regions of the Far Eastern Federal District. According to this method and relevant statistics, constituent entities of the Far Eastern Federal District were compared with control regions of the Siberian Federal District, where these policy tools have not been introduced. Comparable areas had similar socio-economic development trends and migration flows in the period preceding the implementation of the state programmes. To analyse the impact of migration policy changes in 2011–2018, the difference between outflow values of the Far Eastern and synthetic control regions was calculated. The results showed that the average estimated values are negative and significantly different from zero. This indicates a positive effect of new migration mitigation measures on reducing the outflow from the Russian Far East. Future research will separately assess the effectiveness of each migration policy tool implemented in the Far Eastern Federal District.

Contribution of Highly Qualified Employees to Regional Economy

Knowledge and skills concentrated in human capital are increasingly important factors of economic development. However, there is a lack of a methodology for determining, which skills are necessary for the efficient industrial development. To this end, we examine skill requirements of regional employers potentially leading to an increase in economic indicators. Skills in demand were compared with predicted indicators based on a se mantic content analysis of vacancy databases in various regions of the Russian Federation. It was revealed that the list of demanded competencies depends not on a geographical aspect but on a specific profession. An analysis of the obtained data demonstrated that the growth in demand for highly qualified employees in the Russian Federation is correlated with an increase in gross value added of relevant industries. A linear correlation between gross value added per employee and the need for skilled specialists was demonstrated on the example of the transport sector. The proposed methodology can be used by educational organisations for targeted training of specialists, as well as by employers and experts for forecasting medium- and long-term socio-economic development of Russian regions.

Methodology for Assessing the Vulnerability of Participants in Regional Food Markets

The vulnerability of regional food markets is difficult to study due to the lack of a unified approach to analysing the weaknesses of agricultural enterprises, which is necessary for investigating their response to external and internal changes. The study aims to solve this problem by developing an adaptable method for assessing the vulnerability of organisations that produce, process and sell agricultural products in regional food markets. For this purpose, we applied hierarchical mechanisms of integrated assessment for combining various indicators of agricultural enterprises into a single vulnerability score. The present research examines the alcohol market: while this particular sector is represented by a small number of producers, these organisations are usually the largest taxpayers in the agri-food industry, especially in areas of risky farming. As an example, we show how the vulnerability of Permalko JSC (a large producer of alcoholic beverages) has changed because of the COVID-19 pandemic. This company not only satisfies the needs of Perm oblast’s market, but also exports its production to many Russian regions, as well as to near and far abroad. As a result, we propose a new methodology, represented by a set of mathematical formulas, and define its variables. This versatile approach to vulnerability assessment can be adapted for any agri-food enterprise by specifying the parameters. The model is implemented in the dekon software package, which is a web application. The cloud service will provide unified access to all agricultural enterprises.

Regional Innovation Systems in Poland: How to classify them?

The literature emphasises the role of regional and local innovation environment. Regional Innovation Systems show differences in innovation outputs determined by different inputs. Understanding these relationships can have important implications for regional and innovation policy. The research aims to classify Regional Innovation Systems in Poland according to their innovation capacity and performance. The analysis covers 72 subregions (classified as NUTS 3 in the Nomenclature of Territorial Units for Statistics) in 2004–2016. Classes of Regional Innovation Systems in Poland were identified based on a combination of linear and functional approaches and data from published and unpublished sources. It was assumed that innovation systems in Poland differ due to their location in metropolitan and non-metropolitan regions, thus, the Eurostat NUTS 3 metro/non-metro typology was applied for this purpose. Panel data regressions as models with individual random effects were estimated separately for metropolitan and non-metropolitan groups of subregions. The study identified common determinants of innovation outputs in both NUTS 3 types: share of innovative industrial enterprises, industry share, unemployment rate, and employment in research and development. Next, NUTS 3 were classified within each of two analysed types in line with output- and input-indices, the latter being calculated as non-weighted average of significant inputs. Last, the subregions were clustered based on individual inputs to enable a more detailed assessment of their innovation potential. The cluster analysis using k-means method with maximum cluster distance was applied. The results showed that the composition of the classes identified within metropolitan and non-metropolitan systems in 2004– 2016 remains unstable, similarly to the composition of clusters identified by inputs. The latter confirms the changes in components of the capacity within both Regional Innovation System types. The observed situation allows us to assume that Regional Innovation Systems in Poland are evolving. In further research, the efficiency of Regional Innovation Systems should be assessed, taking into account the differences between metropolitan and non-metropolitan regions as well as other environmental factors that may determine the efficiency of innovative processes.

Modelling the Heterogeneity of the Mutual Influence between Russian Regions in the Manufacturing Industry

As factors affecting interregional interactions play an important role in regional economic development. Thus, developing a methodology for assessing these interactions is becoming urgent. The article proposes a methodological approach to analyse the factors influencing possible interactions between Sverdlovsk oblast and other constituent entities of the Russian Federation in the manufacturing industry. It is hypothesised that the elements of an interregional interaction matrix are proxy variables characterising the degree of this interaction. An economic analysis of relations and production chains between Sverdlovsk oblast and other constituent entitles confirmed this hypothesis. First, based on the spatial distribution of manufacturing output in the examined regions, values of an indicator showing the strength of their mutual influence were determined. Second, the impact of economic, infrastructural and institutional factors on the obtained indicator, characterising the inter action between Sverdlovsk oblast and other regions, was assessed using quantile regression. In this case, such a technique was chosen instead of the classical ordinary least squares (OLS) regression that incorrectly estimates the dependencies between the studied variables. This is expressed in the fact that the regression coefficients de pend on q-quantile of the dependent variable. We have revealed that price levels of the examined regions do not affect their possible interactions with Sverdlovsk oblast. Simultaneously, the dissemination of knowledge acts a driver of interaction between the considered regional manufacturing industries. The research findings can be used to prepare strategies, programmes and schemes for the placement and development of industries, considering the potential of Sverdlovsk oblast and other Russian regions.

Quality Assessment of Online Learning in Regional Higher Education Systems

The quality of online learning mechanisms, widely implemented due to the COVID-19 pandemic, is a significant issue for regional higher education systems. The research aims to assess student satisfaction with the quality of online education by identifying discrepancies between their requirements and the actual learning process. In order to examine the gaps between students’ expectations and perceptions, a new approach was proposed based on the integrated use of Gap analysis and SERVQUAL methodology, combining qualitative and quantitative aspects. SERVQUAL questionnaires for measuring student satisfaction with online learning include the following criteria: tangibles, reliability, responsiveness, assurance, empathy. Full- and part-time undergraduates of humanitarian and socio-economic departments of two universities participated in the study. Ural Federal University bachelors, learning via Moodle and Microsoft Teams platforms, could directly communicate with their peers and professors, while students of National Research Nuclear University MEPhI were engaged in massive open online courses (MOOC). As a result, all five criteria were analysed in the proposed model for quality assessment of online learning to reveal the gaps between students’ expectations and perceptions of the educational process. Significant discrepancies in the «empathy» and «responsiveness» criteria in both groups demonstrate low student satisfaction with the quality of communication and individualisation of learning. The research findings can be used to construct resource allocation models for implementing educational programmes and developing support measures for regional higher education institutions.

System for Measuring the Socio-Economic Sustainability of the Eurasian Economic Union

Whether applying to individual countries or unions, the comparability of statistical indicators and their compliance with contemporary international initiatives is a serious problem. In particular, analysis of the macroeconomic indicators used for assessing the sustainability of the Eurasian Economic Union (EAEU) countries has shown that they do not reflect the actual situation. In this regard, the creation of a unified system of indicators for determining the socio-economic sustainability of EAEU member states — as well as the EAEU as a whole — becomes an urgent task. Therefore, the present study aims to refine the system for measuring the socio-economic sustainability of the Eurasian space and develop recommendations for the selection of key parameters. By comparing socio-economic sustainability indicators published by international organisations (UNECE, OECD, Eurostat, CIS Statistical Committee) in the context of the development strategies of individual EAEU countries and the Union as a whole, the authors distinguish between basic and extended indicator types. Basic indicators comprise: the annual consolidated budget deficit; general government debt; annualised inflation rate; contribution of high-tech and knowledge-intensive industries to gross domestic product (GDP); contribution of innovative goods and services to total industrial exports; growth index of the proportion of reconstruction and modernisation investment to total capital investment; fertility rate; life expectancy at birth; poverty rate. Extended indicators include: GDP; economic growth; main international trade; external and national balance of payments; social. The applicability and relevance of the proposed system for measuring the socio-economic sustainability of the Eurasian space is confirmed by statistical analysis of EAEU member state data (including correlation analysis). The results showed that the presented system of indicators reflects the actual development of the EAEU countries, contributing to informed decision-making both at the level of the EAEU member states and at the level of the Union as a whole.

Transformation of Regional Budgetary Independence and Security: Spatial Analysis

The issue of increasing budgetary independence and security is relevant for the majority of territorial systems, both at the regional and municipal levels. It was hypothesised that changes in the structure of regional public debt have a negative impact on their budgetary security. According to this hypothesis, an increase in the proportion of bank borrowing and corresponding decrease in the issue of debt securities by the constituent entities of the Russian Federation leads to a greater overall debt burden on the regional budget. In order to study transformation processes affecting budgetary independence and regional security. We developed a methodology to permit a separate assessment of these concepts. According to this approach, we propose to evaluate the budgetary independence of regional systems in terms of: (1) the balance of the budget (ratio of internal tax and non-tax revenues to budget expenditures); (2) financial dependence on transfers and subsidies from budgets at other levels; (3) budget security, taking into account gratuitous and non-gratuitous transfers. Thus, budget ary security can be assessed in accordance with the public debt dynamics, as well as the level of budgetary debt covered by the region’s own tax and non-tax revenues. The novelty of the presented methodological approach consists in its systematic use of Moran’s I for various spatial weight matrices combined with regression analysis methods based on panel data. Testing this methodology demonstrated the spatial heterogeneity of regional fiscal capacity, highlighting the financial dependence of most regions on federal and other gratuitous transfers. Autocorrelation analysis carried out according to Moran’s I using various spatial weight matrices confirmed the increasing tendency of the budgetary debt of Russian regions towards spatial heterogeneity. Future studies will focus on simulating the influence of various factors on regional budgetary security in order to predict the dynamics of its change.

Meta-regression Analysis of Technical (In)Efficiency in Agriculture: a Regional Approach

While scientific studies have not reached a consensus on the methodology for examining Technical Efficiency (or Inefficiency), the influence of regions appears to be important for efficiency scores. Therefore, this research aims to investigate the empirical procedures for the achievement of more robust results in the analysis of productive efficiency, as well as to evaluate the effect of the location of farms on such efficiency. The goal was to check whether the most developed regions are the most efficient. Meta-regression analysis provides an adequate method for an accurate assessment of both situations. This technique was applied based on a database of 166 observations on the agricultural sector from countries around the world, published in the period 2010–2017. The criteria used for the database collection and for the conceived model were not previously used and, thereby, enrich the discussion on the topic. The procedure aims to check the variation in the Mean of Technical Inefficiency and conduct an analysis using Quasi-Maximum Likelihood Estimation. The regressions showed that the Mean of Technical Inefficiency could be mainly explained by data, variables, employed empirical models and the region of study. The studies that focus on farms of developed countries present the lowest Mean of Technical Inefficiency, while studies for developing or low-income countries exhibit the opposite. Therefore, for future research on productive analysis, we suggest empirical procedures aimed at achieving robust results that take into account specific regional characteristics of farms.