The impact of R&D and knowledge spillovers on the economic growth of Russian regions

2018 ◽  
Author(s):  
Maria Kaneva ◽  
Galina Untura
Keyword(s):  
Economic Growth ◽  
Knowledge Spillovers ◽  
Russian Regions ◽  
The Impact

scholarly journals Phenomenon of Structural-Technological Proximity and Knowledge Spillovers between Russian Regions

2020 ◽  
Vol 16 ◽  
pp. 1254-1271
Author(s):  
Galina A. Untura ◽  
Maria A. Kaneva ◽  
Olga N. Moroshkina
Keyword(s):  
Economic Growth ◽  
Russian Federation ◽  
Knowledge Spillovers ◽  
Knowledge Spillover ◽  
Spatial Proximity ◽  
Russian Regions ◽  
Economic Activities ◽  
Novosibirsk Region ◽  
The Russian Federation ◽  
The Impact

International theoretical and empirical studies have shown that regional development and economic growth largely depend on spatial and non-spatial proximity of regions, which generates knowledge spillovers. We developed a methodological approach to measuring and visualising spatial and structural-technological proximity affecting regional knowledge spillovers. Moreover, we tested the techniques of the cartographic visualisation of the proximity of Russian regions. Further, we analysed foreign and domestic approaches to studying spatial and non-spatial proximity and obtained new results. We described the stages constituting a methodology for the quantitative assessment of different types of regional proximity. Additionally, we proposed a method for constructing a typology of regions based on the coefficients of the non-spatial proximity matrix, calculated according to the indicator “gross value added” for 15 sectors of the Russian National Classifier of Economic Activities (OKVED) for Russian regions. Using the data for the Novosibirsk region in 2005 and 2016, we applied methodological techniques for measuring and visualising geographical and structural-technological proximity (STB) of a region in relation to other constituent entities of the Russian Federation. The Novosibirsk region is located in the middle of the country and has a diversified structure of economic activities and science. For this particular region, there has been an increase in the likelihood of the emergence of knowledge spillover channels with various European regions of Russia and some regions of the Urals and the Far East. Proximity matrices can be used in econometric studies to test hypotheses about the impact of different forms of proximity on regional economic growth. Recommendations to enhance knowledge spillover coincide with the proposals to support the areas of innovative development stated in The Strategy of Spatial Development of the Russian Federation for the period until 2025.

The impact of foreign direct investment on urban-rural income inequality

2016 ◽  
Vol 8 (3) ◽  
pp. 480-497 ◽  
Author(s):  
Chunlai Chen
Keyword(s):  
Economic Growth ◽  
International Trade ◽  
Income Inequality ◽  
Fixed Effects ◽  
Knowledge Spillovers ◽  
Employment Creation ◽  
Content Type ◽  
Rural Income ◽  
Urban Rural ◽  
The Impact

Purpose The purpose of this paper is to analyse the impact of foreign direct investment (FDI) on urban-rural income inequality in China. Design/methodology/approach This study uses the provincial-level panel data and employs the fixed-effects instrumental variable regression technique to investigate empirically the impact of FDI on urban-rural income inequality in China. Findings The study finds that while FDI has directly contributed to reducing urban-rural income inequality through employment creation, knowledge spillovers and contribution to economic growth, FDI has also contributed to increasing urban-rural income inequality through international trade. Practical implications The study has some policy implications. First, as the study finds that FDI not only contributes to reducing urban-rural income inequality through employment creation, knowledge spillovers and contribution to economic growth, but also contributes to increasing urban-rural income inequality through international trade, therefore, apart from improving local economic and technological conditions to attract more FDI inflows, China should re-design FDI policies by shifting away from encouraging export-oriented FDI to encouraging FDI flows into the industries and sectors in line with China’s overall economic structural adjustments and industrial upgrading. Second, policies should focus on increasing investment in infrastructure development and in public education, which not only can reduce urban-rural income inequality but also can attract more FDI inflows. And finally policies should be designed to accelerate urbanisation development by focusing on urban-rural integrated development, household registration system reform and proper settlement of rural migrants in urban areas, thus reducing urban-rural income inequality. Originality/value The paper makes two major contributions to the literature. First, the paper adopts the fixed-effects instrumental variable regression technique to deal with the endogeneity issues in estimating the impact of FDI on urban-rural income inequality, producing more consistent estimates. Second, the paper investigates not only the direct impact of FDI on urban-rural income inequality through the effects of employment creation, knowledge spillovers and contribution to economic growth, but also the indirect impact of FDI on urban-rural income inequality through its activities in international trade, adding new empirical evidence to the sparse literature on the impact of FDI on income inequality in China.

scholarly journals ASSESSMENT OF THE IMPACT OF INCOME INEQUALITY ON ECONOMIC GROWTH IN RUSSIAN REGIONS

2021 ◽  
Vol 2 ◽  
pp. 106-110
Author(s):  
Rogneda Vasilyeva ◽  
Oleg Mariev ◽  
Elena Ignatieva ◽  
Alla Serkova
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Income Inequality ◽  
Capital Investment ◽  
Cultural Development ◽  
Russian Regions ◽  
Socio Economic Development ◽  
Per Capita ◽  
Fixed Capital Investment ◽  
The Impact

Inequality in the distribution of income of the population has a certain impact on different aspects of the economic and socio-cultural development of countries and regions. This inequality arises due to a number of factors as the current nature of the production specialization, the availability of production and economic infrastructure, the achieved level of development of the social sphere, socio-cultural, demographic, and other factors. The main objective of this study is to assess the nature and extent of the impact of income inequality in the Russian regions for the subsequent justification of the directions of socio-economic development. We conducted an econometric analysis of the impact of intraregional income inequality (the Gini coefficient), fixed capital investment per capita, and average per capita consumer spending on one of the main indicators of regional economic growth (GRP) per capita was carried out. The model is based on panel data for the period 2012-2018 for 85 regions of the Russian Federation. The results of the study confirm two of three hypotheses. As prospects for further research, it is proposed to consider the impact of inequality in the distribution of household income on economic growth for different groups of regions, including resource-type regions and regions with a predominance of manufacturing industries, as well as for leading regions and regions with a relatively low level of socio-economic development.

Social Capital as a Factor of Economic Growth in the Regions of Russia

2019 ◽  
Vol 14 (5) ◽  
pp. 124-149 ◽  
Keyword(s):  
Economic Growth ◽  
Social Capital ◽  
Economic Development ◽  
Growth Rates ◽  
Generalized Method Of Moments ◽  
Sociocultural Factors ◽  
Russian Regions ◽  
Least Squares Regression ◽  
Economic Growth Rates ◽  
The Impact

This paper examines the influence of sociocultural factors of economic growth on economic development of the Russian regions. The article analyses the influence of various forms of social capital according to James Coleman (norms of trust between individuals, horizontal ties, social norms and values) on economic growth rates of the Russian regions. The paper uses an augmented neoclassical model of economic growth to test the hypotheses about the impact of the initial social capital distribution on the subsequent GRP growth rates in 2007–2016. Particular attention is paid to the selection of relevant tools for measuring the level of social capital of the Russian regions. The empirical specifications of the proposed theoretical model of regional economic growth were evaluated using the two-stage least squares regression (2SLS); the robustness check was carried out using the system generalized method of moments (system GMM). The results of econometric analysis show that the initial spatial distribution of generalized trust does not have a statistically signifi cant effect on economic development. At the same time, the activity of lobbying groups (Olson groups) reduces the rate of economic growth in the regions of the Russian Federation. Increasing the level of civic cooperation (the willingness of citizens to unite to solve their own or social problems in the region) is associated with higher rates of economic development. For the selected study period, the economic signifi cance of sociocultural factors is marginal relative to the significance of the fundamental neoclassical growth factors. Unlocking the potential of sociocultural factors of economic growth may suggest activating the processes of structural transformation of the Russian economy by increasing the economic importance of the private sector and SME segment.

The impact of science, innovation and concentration of production enterprises on the economic growth in the Russian regions

2019 ◽  
Vol 15 (12) ◽  
pp. 2327-2343
Author(s):  
G.A. Untura ◽  
◽  
M.A. Kaneva ◽  
A.A. Zabolotskii ◽  
◽  
...  
Keyword(s):  
Economic Growth ◽  
Russian Regions ◽  
Science Innovation ◽  
The Impact

scholarly journals Does income inequality matter for CO2 emissions in Russian regions?

Equilibrium ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. 533-551
Author(s):  
Natalia Davidson ◽  
Oleg Mariev ◽  
Sophia Turkanova
Keyword(s):  
Economic Growth ◽  
Income Inequality ◽  
Co2 Emissions ◽  
Environmental Kuznets Curve ◽  
Value Added ◽  
International Perspective ◽  
Kuznets Curve ◽  
Russian Regions ◽  
Fixed And Random Effects ◽  
The Impact

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.

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