Search by keyword: innovations

CONTRIBUTION OF NATIONAL PROJECTS TO THE SOCIO-ECONOMIC DEVELOPMENT OF RUSSIAN REGIONS

Russia’s national projects are having an increasingly significant impact on the country’s socio-economic development each year. The aim of this study is to examine the contribution of national projects, grouped by region and ba­sed on indicators of their implementation, to changes in the socio-economic development at the regional level, and to identify the gap between leaders and laggards in development. The novelty of this study lies in the attempt to assess the contribution of national projects to the socio-economic develop­ment from a regional perspective. It is shown that national projects are a rela­tively new but effective method for stimulating the socio-economic development of regions. The positive impact of national projects is noted, which consists in the formation of a more favorable economic environment in the regions according to specific indicators, such as, for example, gross regional product. One of the key factors slowing down the socio-economic development of re­gions is population decline, which the national projects included in the “Hu­man Capital" block are aimed at counteracting.

Dorofeeva L. V. dorofeevalucy@gmail.com

Nazarova E. A. Jane.nazarova@mail.ru

Keywords: national projects socio-economic development innovations regional groupings competitive potential

ASSESSING THE IMPACT OF EXTERNAL FACTORS ON THE DIGITAL MATURITY OF GOVERNMENT AGENCIES IN THE REGIONS OF THE RUSSIAN FEDERATION

There remains a pronounced interregional differentiation in the level of digital development across the Russian Federation, which necessitates a comprehensive analysis of the factors influencing the digital maturity of public administration bodies in the country’s regions. This article offers a quantitative assessment of the impact of external socioeconomic, institu­tional, and technological factors on the level of digital maturity of government agencies in the constituent entities of the Russian Federation, as well as identifies statistically significant predictors based on panel data models.
Within the framework of a PEST analysis, 38 macro-level factors poten­tially affecting digital maturity were examined, of which 17 measurable indica­tors were selected and grouped into categories: economic conditions of the re­gion; public support and investment in the digital sphere; education and employment levels; innovation development; and the availability of IT infra­structure. A panel data set was compiled for 84 regions of the Russian Fede­ration for the period 2021-2023, and fixed effects models were constructed.
The analysis confirmed the statistical significance of such factors as gross regional product, budget expenditures, education level, innovation activity of organizations, number of employees in the ICT sector, and citizen satisfac­tion with digital platform solutions. The findings demonstrate that the digital maturity of regional public authorities is shaped by a complex set of external conditions, which should be taken into account when developing digital trans­formation strategies.

Ushakov M. O. moushakov@hse.ru.

Zhatikova D. V. dvzhatikova@edu.hse.ru.

Ataeva A. G. aataeva@hse.ru.

Styrin E. M. estyrin@hse.ru.

Keywords: digital maturity external factors taxes PEST analysis digital transformation region innovations

WHO IS AT RISK? FACTORS OF SANCTIONS RISKIN RUSSIAN REGIONS

This study aims to identify groups of Russian regions by their level of sanctions risk prior to the imposition of sanctions and to test the actual exposure to sanctions of these groups after 2022. The application of k-means clustering allowed us to identify three clusters of regions based on their level of sanctions risk using 2021 data: regions with high, medium, and low sanc­tions risk. Data on the number of sanctions imposed on enterprises in the re­gions by the end of 2023 confirmed the validity of the cluster allocation. The average number of sanctions imposed by the end of 2023 on enterprises in regions belonging to the high-sanctions-risk cluster is 129. For the cluster of regions with medium sanctions risk, this figure is 28, and for the low-risk cluster, it is 4. It was found that reliable predictors of a high level of sanctions pressure are such indicators of the regional economy as the region’s enga­gement in trade with overseas countries and the share of the manufacturing industry in the gross regional product. At the same time, economic diver­sification does not always contribute to a lower risk of sanctions pressure.The results of the study have high practical significance for regional econo­mic policy.

Voytenkov V. A. vvoytenkov@hse.ru

Urazbaeva A. R. aurazbaeva@hse.ru

Demidova O. A. demidova@hse.ru.

Keywords: sanctions sanctions risk innovations machine learning clustering trade openness economic diversification manufacturing industry

Workforce Productivity in Russian Regions: Comparative Analysis

A comparative analysis of workforce productivity data in Russian regions is carried out. The paper discovers possibilities to strengthen regional factors inducing a rise in workforce productivity. It presents results from the analysis of the dynamics and interregional differentiation of workforce productivity based on statistics published by the Russian Federal State Statistics Service (Rosstat) and estimates of workforce productivity levels in regions and aggregate types of economic activity. Interregional differences in workforce productivity levels exhibit a tendency to decrease. An assessment of hourly productivity by types of economic activity revealed the most significant interregional differences in mineral production, construction, and agriculture. The article provides results from the comparative analysis of existing jobs in Russia in terms of their industrial distribution, workforce productivity, and salary levels. The paper gives a critical overview of the method to determine high-performance workplaces developed by Rosstat. We show that the growth rate in the number of high-performance workplaces calculated with this method is loosely related to the dynamics of workforce productivity and real income of the population. Directions to promote regional factors that increase workforce productivity suggested in government decrees are examined. Basing on interregional migration data in Russia, we show enabling and constraining effects of measures designed to enhance labor mobility

Miheeva N. N. mikheeva_nn@mail.ru

Keywords: innovations производительность труда межрегиональная дифференциация высокопроизводительные рабочие места занятость в регионах мобильность трудовых ресурсов

Regional disparities in Russia: ecological aspect

The paper makes an ecointensity analysis of the economies of the RF regions over the crisis and post-crisis periods. We apply the Gini coefficient, and Atkinson and Theil indices. Having made a comparative analysis of the results obtained, we can state that according to the indices under study, there is a significant regional inequality observed.

Klevakina Ye. A. bedew@yandex.ru

Zabelina L. A. i_zabelina@mail.ru

Keywords: gross regional product innovations inter-regional inequality assessment regional inequality

Spatial structure of the Russian economy: analyzing its dynamics through application of genotyping methods

The paper analyzes a range of regional indicators and composite indices characterizing the development in the subjects of the Russian Federation over 2000-2007 and 2008-2010. We offer a technique based on the spatial and temporal laws of socio-economic development and designated for building generalized curves (genotypes) to describe regional development. We also present our forecasts of how the RF multiregional system could develop within the context of the given genetic scenario

Suspitsyn S. A. susp@ieie.nsc.ru

Keywords: regional economy innovations regional economy development scenarios Russian regions multiregional system

HowRussianregionscomeoutoftherecession

The paper analyzes the data of current statistics provided by the Federal Statistics Service of the Russian Federation. There were the economic drop observed in the development of different groups of the RF regions and different economic activities over 2008-2010. The assessment of scales of regional growth and recovery periods are also presented

Suspitsyn S. A. susp@ieie.nsc.ru

Keywords: regional economy economic crisis innovations regional economy

Assessing the innovation system in Russian regions: present state and further development

The current techniques for assessment of innovations do not completely reflect the regional specifics of innovation activities. This study offers a system of key indicators which would allow assessing the level of the development of a regional innovation system. We present a classification of the RF regions by the indicators proposed, and a comparative analysis of the SFD regions.

Serdyukova Yu. S. serdukova@ieie.nsc.ru

Valieva O. V. o_valieva@mail.ru

Suslov D. V. suslov@nsu.ru

Starkov A. V. starkov@int-park.com

Keywords: innovation innovations Russian regions tools of governmental support system of indicators

Income inequality in Russian regions: comparative analysis

This article reviews the domestic and foreign studies which empirically analyze inter-regional income inequality in Russia. The studies are grouped according to the statistical approaches applied in these studies (cross-sectional analysis, time series analysis, and distribution dynamics analysis). The adequacy of the techniques used and data analyzed is discussed. We also consider the issue of relationship between studying inter-regional income inequality and policy implications.

Gluschenko K. P. glu@nsu.ru

Keywords: innovations gross regional product Russian regions inter-regional inequality incomes

Spatial externalities as a source of economic growth

On the base of the Russian data, we undertook an empirical testing of a model where the spatial externalities generated by regional growths are considered as a source for development of neighboring territories. As our results show, such externalities do affect the other regions' growth rates but the character of such influence in the western Russian regions differs from that in the eastern ones.

Kolomak Ie. A. ekolomak@academ.org

Keywords: spatial externalities spatial econometrics innovations

Full-text issues of the Journal in PDF format are available since 2006 (except for the ones published within the last year)

pdf-icon.png