Economic Growth In Russian Regions Research Articles

Correlation between income inequality and economic growth in Russian regions: new results based on the Granger causality test

The issue of income inequality is highly relevant in scientific literature. It is caused both by the population’s pursuit of achieving an acceptable level of social justice specific to a particular society and by the property, which is often attributed to income inequality, to negatively influence economic development and growth. This article conducts an analysis of cause-and-effect relations between income inequality in the Russian regions (measured by the Gini index) and the level of gross regional product (hereinafter referred to as GRP) per capita. The primary research method employed is the Granger causality test. The research is based on data from the Federal State Statistics Service on the socio-economic development of Russian regions. Direct and reversal causality tests were performed, revealing that GRP per capita influences income inequality, but not vice versa. Moreover, the logarithm of GRP per capita exhibits a bidirectional relationship with the Gini index for Russian regions. On the basis of the obtained results, it is concluded that for effective management of the issue of regional income inequality, it is advisable to use indirect methods of financial regulation instead of the direct ones and influence income inequality through indicators of GRP per capita in Russian regions, thereby creating conditions for an increase in the standard of living and average income.

Poverty, Demographic Development and Economic Growth in Russian Regions: Assessing Interrelationships

Poverty, Demographic Development and Economic Growth in Russian Regions: Assessing Interrelationships

Human capital quality and its impact on economic growth of Russian regions

Purpose: is to empirically substantiate the impact of human capital quality on the economic growth of the regions of Russia on the basis of theoretical and methodological generalization of its main aspects.Methods: along with traditional methods, specific methods were used, such as content analysis, methods of expert assessments and comparative analysis, and the calculation and graphic technique of Xiang-Yeaple, which allowed to identify the state of human capital quality, as well as establish its optimal structure suitable for dynamic economic development.Results: the cognitive and non-cognitive parameters of human potential are established as a realistic factor in the dynamics of gross regional product that determines the future pace of economic development. A comparative analysis of the labor demand and supply elasticity coefficients has revealed the degree of impact of its quality in ensuring the corresponding trends of economic growth. It was proven that significant investments in human capital and high levels of its development represent only a factor of ensuring economic growth and don’t guarantee its achievement. Recommendations for ensuring the development of labor potential as determinant of economic development, the growth rates of which largely depends on the human capital quality.Сonclusions and Relevance: the Russian economy should focus on the formation and development of high-quality human capital through talent-fueled innovation by reforming the existing education system and assessing scientific potential in order to optimize the labor and branch structure suitable for high-quality economic growth. Human capital should be structured considering the parameters of its quality, the level of available labor potential, and the types of activities that require advanced knowledge for systemic economic growth.

The Knowledge Economy and Digitalization: Assessing the Impact on Economic Growth of Russian Regions

The Knowledge Economy and Digitalization: Assessing the Impact on Economic Growth of Russian Regions

Innovation and credit market deepening: Evidence from Russian region

We investigate the impact of credit market deepening on innovation, considering the role of investment risk and investment potential in the context of Russian regions, analysing the panel time series data extracted from the Federal Statistics Department of the Russian Federation and using the method of moments quantile regression. Our baseline findings demonstrate that credit market development spurs innovation in the sample regions in all quantiles (q10–q90), and the credit market has a positive impact on innovation, regardless of whether investment risk is lower or higher. In addition, we reveal a U-shaped relationship between innovation and regional economic growth in Russian regions. We also observe reductions in imports and exports and a boosting effect of increased employment on innovation. We propose several potential policy measures and practical conclusions based on our findings.

Intensive and Extensive Margins of Export: Determinants of Economic Growth in Russian Regions under Sanctions

The impact of foreign trade on the Russian economy’s growth remains debatable. In 2014, the economy faced initial sanctions, leading to export restructuring and affecting growth. In 2022, a second unprecedented wave of sanctions necessitated export restructuring and intensified the challenge of sourcing economic growth. This study evaluates the impact of intensive and extensive export margins on Russian regions’ growth from 2015 to 2021 and discusses post-2022 implications. It is hypothesised that new export goods and markets are vital for economic growth in Russian regions. The study shows that both intensive and extensive margins are positively related to the level of development in Russian regions, and developed regions with diversified economic structures had higher values of export margins. The methodology uses panel regression with random and fixed effects. The empirical results show Russian regions’ market share in the products they export and in the countries where they export (i. e. intensive product and geographic margin) is important for the economic growth of Russian regions, while the results for extensive margin are ambiguous. The obtained findings have implications for industrial policy, which should prioritise the development of measures aimed at supporting existing exporting companies in expanding their presence in familiar markets. The task of export diversification should primarily be addressed through working with existing exporters and export products, while the export of innovative products should be viewed as a gradual evolutionary process within the framework of long-term planning.

Development Priorities for the Regional Innovation System Based on the Best Available Technologies

At the present stage one of the most important factors in the economic growth of Russian regions is the production processes modernization based on the best available technologies (hereinafter—BAT), ensuring the reduction of the negative impact on the environment in cost-effective ways. The most important conditions for the successful implementation of BAT at regional enterprises is the creation of general institutional conditions at the all-Russian level and the supply of enterprises with domestic technologies meeting the criteria of the best available technology. Over the past several years, large-scale work has been carried out in Russia to amend legislation, prepare BAT reference documents, and form the institutional conditions for their implementation. However, sustainable outcomes in specific regions will require the further development of regional innovation systems, consistent with the needs of local enterprises in BAT. The article proposes a general regional mechanism for managing the sustainable development of an innovation system based on BAT. For its successful implementation, a set of practical recommendations for the Rostov region has been formed. Within the framework of the innovation regional infrastructure it was proposed to create a new institute for the implementation of BAT—the Regional BAT competence center, priority areas for the development of potential and promising BAT in the region were identified, a general pattern of interaction of the Regional BAT competence center with other participants in the process was developed.

A theoretical approach to understanding the budget tools for stimulating economic growth in russian regions

A theoretical approach to understanding the budget tools for stimulating economic growth in russian regions

Тестирование альтернативных моделей регионального экономического роста: грани возможного (о книге А.Г. Исаева «Экономический рост российских регионов: экзогенные и эндогенные источники»)

In this work we analyse the main results on the study of the factors of the regional economic growth in Russia that are presented in ‘Economic Growth of Russian Regions: exogenous and endogenous Sources’ by A.G. Isaev. The emphasis is made on the features of the instrumental base of the study. A.G. Isaev makes an attempt to test alternative macroeconomic models, adapted to varying degree to the tasks of interpreting the phenomena of regional growth, which inevitably raises questions about the possibilities of gaining synthetic knowledge based on such testing. We discuss two problems using the example of the results of conditional convergence assessment, verification of Verdoorn’s law, and determination of the potential for generating endogenous impulses in regional economies, presented in the book. The first problem of equifinality is common to all studies of economic dynamics, regardless of the objects that are considered in them, whether it is the economies of countries or regions. The second problem of determining the sources of spatial dependence and options for taking them into account is specific for studies of regional economic growth. The general conclusions are that the task of obtaining meaningful, internally consistent conclusions based on neoclassical and Keynesian models of economic growth is not trivial; the problem of equifinality for the models under consideration is imaginary, since their estimates of conditional convergence coincide at least on a qualitative level and they cannot tells us anything specific about the trends of interregional income inequality; there are issues arising from the use of neoclassical models that are still at the forefront of research on regional economic dynamics, including the issues related to the choice of the method of taking into account spatial dependence, the solution of which requires a certain reorientation of research work from the detection of particular causal effects to the analysis of universal patterns; models that are unpopular but at the same time transparent in the way they describe the channels of interregional influences can be useful in studies of the mechanisms of generation and absorption of impulses in the economy of the region

Эффекты и риски цифрового качества жизни населения в регионах России

Widespread digital transformation significantly changed people’s quality of life. We hypothesise that the digital component of people’s quality of life had a positive but differential impact on economic growth in Russian regions during 2015–2019. Moreover, economic and institutional risks occurring at the current stage of digital transformation could negatively affect economic development. The research pays special attention to the institutional factor, namely, project management quality and its influence on real gross domestic product (GDP) per capita in Russian regions. Methods of economic research were used such as index, rating, expert evaluation methods as well as regression and panel data models (including those with dummy variables). Transformation assessment was based on an integral index proposed by the authors called the Russian regional index of digital component of people’s quality of life (RRIDCPQL). The value of this digital index was increasing during 2015– 2019. The hypotheses of statistically significant influence of the digital quality of life, regional and temporal unobserved factors on real GDP per capita in 2015–2019 were confirmed. However, the study rejected the hypotheses of the positive impact of digitalisation on the unemployment rate and on the decrease in the share of government employees. Positive influence of digitalisation on the divorce rate was revealed while its negative influence on economic criminality and real income per capita of the population was partially confirmed. The importance of project management quality of the program “Digital economy of the Russian Federation” for regional development was demonstrated. The research results presenting new data on the growth of digital economy can be used to adjust the implementation of digital projects in Russian regions.

Resilience of the resource regions for sustainable development in Russia

The economic growth of Russian regions is one of the key indicators for the country. The regional economies have significant differences in the structure of production and services, therefore, ensuring economic growth depends on various factors of the internal structure and external influence. In this regard, the task of searching for growth factors and risk factors for the sustainable development of Russian regions becomes important. The aim of this work is to assess the resilience of the economy of energy resource regions of Russia to changes in the fiscal energy policy of the state. The authors found that such factors exert the strongest influence as tax yield and the balance of tax payments. Moreover, the energy resource regions of Russia are resilient to these factors. Considering the tax security of the regional budget, we can say that it has a fairly strong impact. The regional budget deficit and the level of budgetary provision have little impact on the economic growth of oil-producing regions. From which the authors conclude that the energy regions are resilient to these factors. The regional budget deficit has the smallest impact. After division into clusters, it was revealed that the main oil-producing regions of Russia turned out to be resilient to changes in the fiscal energy policy of the state. Only eight regions of the considered ones turned out to be resilient: Krasnoyarsk Krai, Tyumen Oblast, Astrakhan Oblast, Republic of Sakha, Kaliningrad Oblast, Sakhalin Oblast, Novosibirsk Oblast and Omsk Oblast.

Does income inequality matter for CO2 emissions in Russian regions?

Research background: Intensive economic growth in Russian regions during recent decades has been associated with numerous environmental issues, particularly increasing CO2 emissions, as well as income inequality. To achieve sustainable development, it is necessary to resolve these issues.
 Purpose of the article: To shed light on the impact of income inequality on CO2 emissions based on Russian regional data covering the years 2004?2018.
 Methods: Gini index and decile dispersion ratio are used to measure income inequality. To study the impact of income inequality on CO2 emissions in the Russian regions, we estimate econometric models with fixed and random effects and apply GMM method. We test the hypothesis of the environmental Kuznets curve to determine the impact of economic growth on CO2 emissions.
 Findings & value added: The results show that CO2 emissions increase in tandem with growth in income inequality between 10% of people with the lowest income and 10% of people with the highest income. Simultaneously, CO2 emissions decrease with growth of Gini coefficient. The hypothesis of the Environmental Kuznets Curve was confirmed based on GMM method. Our findings underscore that the activities of the extraction and manufacturing sectors, as well as energy consumption, increase CO2 emissions. The chief significance of this paper is the finding that large income gap between extremely rich and extremely poor population cohorts increases CO2 emissions. This implies that economic policy aimed at reducing income inequality in Russian regions will also reduce CO2 emissions, especially if accompanied by increased use of environmentally friendly technologies. From the international perspective, our research can be extended to study other countries and regions.

The impact of public and private investments on the economic dynamics of Russian regions

Subject. The article deals with the comparative analysis of the impact of various sources of financing on the economic growth of Russian regions. Objectives. It focuses on evaluating the impact of public and private investments on the growth rates of real GRP in Russian regions. Methods. The study employs a regression analysis of panel data of Russian regions, using models with fixed and random effects, and a generalized method of moments, a modification of the Mankiw–Romer–Weil's model, which distinguishes investments from the Federal budget, consolidated budgets of Federal subjects of Russia, foreign, and private investments. Results. The study reveals that the attraction of foreign investments has the greatest positive impact on the economic growth of Russian regions. Federal budget investments do not stimulate private investments or contribute to the economic growth of regions, which is related to the priority of Federal investments aimed at achieving socio-political rather than economic goals. Conclusions. Increasing the growth rates of the economies of Russian regions requires consistent work to attract foreign investments, which is complicated by the current geopolitical situation. Measures are necessary to improve the efficiency of budget investments, including the implementation of modern approaches to quantifying the costs, benefits and risks of socially significant investment projects in the practice of public financial management, and sharing the risks of public investments with private capital through the development of public-private partnership mechanisms.

On the Relationship between Health Capital and Economic Growth in Russian Regions (2013–2018)

Over the last few years in the Russian economy and politics, it was generally agreed that the population’s health is one of the drivers of the economic growth. While little research has been done on the relationship between health capital, health care costs and economic growth, there is no generally accepted model in economic theory supported by empirical tests for individual countries and regions that would explain the relationship between these variables. This study aims to address this gap and quantifying the impact of health capital and health care costs on the regional economic growth in 2013–2018 within the economic growth model with endogenous technological progress. The authors constructed two specifications of the Arellano-Bond model for the dependent variable GRP per capita growth rate. The simulation results have made it possible to conclude that the accumulation of health capital leads to increased economic growth in the Russian regions. Simultaneously, an increase in government spending on health care at a fixed level of health capital did not result in an increase in GRP per capita growth rate in 2013–2018, which a number of factors can explain, i.e. general focus of public health expenditure on maintaining a favorable epidemiological situation and infrastructure of industries not directly related to individual health as well as possible insufficient level of human capital accumulation in the regions. Further research will focus on assessing the impact of health capital and health care costs in an extended model to include the level of human capital.

Neural network modeling of tourism development as a factor of sustainable economic growth in Russian regions

The features of the development of the tourism sector in the regions of the Russian Federation, which have an impact on the socio-economic development of the country, have been investigated. Analysis of the current state of the tourism sector, classified as the main types of economic activity, is relevant and important for increasing the competitiveness of the regions of the Russian Federation and ensuring the economic security of the state. The study is aimed to model and analyze tourist cluster formations in Russia. The study of tourist activity in the regions of Russia based on the indicators of the database of the Federal State Statistics Service was carried out using a new promising approach - cluster analysis using the scientific and methodological apparatus of artificial neural networks. The distribution of Russian regions into five tourist clusters has been obtained as a result of clustering multidimensional data using neural networks - self-organizing Kohonen maps, which are focused on self-study, and modern information technologies. In neural network modeling, the six-dimensional space of tourism development indicators was mapped, taking into account the topology, into a two-dimensional space, which made it possible to visualize the results of grouping regions by tourist clusters. The features of the development of the tourism sector in the regions of the Russian Federation have been revealed by the totality of the considered indicators The obtained results state that there is a strong variation in the number of regions by tourist clusters and the ametric nature of the development of tourist activity in the regions of Russia. The results of the study are of practical significance for the strategic planning of the tourism sector development, which ensures the development of domestic and inbound tourism. Analysis of the functioning of the tourism sector in the regions of the Russian Federation allows concluding the necessity to take a set of measures to stimulate effective investment activity in a number of tourism clusters, harmonizing the strategies of the state and business, which will contribute to the renewal and competitiveness of this type of economic activity.

Assessment of the Contribution of Inter-Territorial Interaction in the Development of the National Economy

Determination of the main indicators of economic growth is a key research question. In the course of solving this problem, many scientists agree that one of the drivers of economic development is interregional interaction. This article contains the results of a quantitative assessment of the role of interregional interaction for the Russian economy. The study is based on a modification of the Solow economic growth model which includes the level factor of interregional interaction. For a quantitative assessment of the effects of interregional interaction on economic development, a set of factors was determined that make it possible to assess the advantage that localization in a particular region can give to economic agents. The selected indicators have a direct impact on the potential and intensity of interregional interaction. The database for assessing the coefficients of the models and calculating the index of interregional interaction was formed on the basis of data from the website of the Federal State Statistics Service for the period from 2010 to 2018 for 83 regions of Russia. To select the best model of economic growth, considering interregional interaction, the authors evaluated different types of models: fixed effects model, time fixed effects model, random effects model, and time random effects model. The thesis about the importance of interregional interaction as one of the most important factors of production in modern Russia has found its empirical confirmation: the share of interregional interaction in ensuring the economic growth of Russian regions in the years 2015–2018 averaged 33%. The developed model of economic growth and the consideration of interregional interaction is universal and can be applied to various administrative-territorial units.

Разработка методических подходов к оценке эффективности инвестиций в инфраструктуру с учетом зарубежного опыта (Development of Methodological Approaches to Assessing the Effectiveness of Investments in Infrastructure, Taking Into Account Foreign Experience)

Russian Abstract: В работе предложены методы оценки эффективности инфраструктурных инвестиций на макроэкономическом и проектном уровнях. С использованием панельных данных и методов пространственной эконометрики изучено влияние развития инфраструктуры на экономический рост в российских регионах. Оценено влияние создания высокотехнологичных перинатальных центров на снижение младенческой и материнской смертности с учетом эффекта кривой обучения. Разработаны методические подходы к оценке информационных рисков и рисков отклонения фактической выработки электроэнергии от проектной при реализации проектов сооружения атомных станций. English Abstract: The study proposes methods of infrastructural investments evaluation at macroeconomic and project levels. The impact of infrastructure development on economic growth in Russian regions has been studied using methods of spatial econometrics and panel data. The impact of high-tech perinatal centers opening on reducing infant and maternal mortality has been evaluated considering the effect of learning curve. The techniques to assess information risks and risks of deviation of actual electricity generation from the projected level of nuclear power plant construction projects have been developed.

Population shrinkage and economic growth in Russian regions 1998–2012

AbstractThis paper analyses the relationship between demographic decline and economic development in Russian regions in the period 1998–2012, demonstrating how shrinking regions undertook different economic growth patterns. In some cases, population decline was associated with an effective restructuring of the regional economic system. Successful shrinking regions appear to have, at the beginning of the period, a higher endowment of private capital and a higher share of the young population than the other shrinking regions. In 2012, these differences were even broader, suggesting the potential occurrence of a vicious cycle for the unsuccessful shrinking regions, for which the process of depopulation did not probably stop here.

Friends or Foes? The Effect of Governor-Siloviki Interaction on Economic Growth in Russian Regions

Although many scholars have analyzed the role played by the siloviki in Russian politics, they usually focus on the presence of siloviki in the federal elite or the pressure they exerted on business. In this article, we use new data on the appointments of regional governors and the heads of regional departments of the Federal Security Service (ufsb), as well as data on regional economic growth from 2005 to 2017, to examine how decisions by the Kremlin with respect to the appointment of key regional siloviki have affected economic development in Russian regions. We find that regions where the governor-siloviki relationship has been stable over time also display higher rates of growth. We then investigate whether regional fsb heads are specifically appointed to start investigations on regional governors, but do not find a statistically significant relationship. Finally, we show how a number of newly appointed political heavyweights among Russia’s governor corps have been given their “own” silovik to support them in their region.

Effect of Health Capital on the Economic Growth in Russian Regions

Effect of Health Capital on the Economic Growth in Russian Regions