Pub Date : 2023-01-01DOI: 10.17059/ekon.reg.2023-3-12
E. A. Kolomak, A. I. Sherubneva
While agglomeration effects are an essential element of the economic environment determining the decision-making on the capacity allocation and implementation of infrastructure projects, their impact in the East of Russia is questioned. Development conditions of Novosibirsk oblast can have a contradictory effect on agglomeration forces. The paper aims to obtain quantitative estimates of the impact of agglomeration effects on enterprise performance by analysing the SPARK-Interfax database for 2019. To this end, the visualisation of the spatial distribution of the sample data, average output and profit characteristics was performed. Additionally, the econometric analysis of the influence of agglomeration factors on enterprise performance was conducted. As a result, the microeconomic analysis showed a statistically significant impact of agglomeration effects on the productivity of firms in Novosibirsk oblast. A two-fold increase in the distance to the regional capital leads to a reduction in output and profitability of enterprises by 3.5 %. This finding supports the development and implementation of private and public infrastructure projects. The analysis demonstrated a higher differentiation of profit indicators in cities, as well as a significant drop in performance and efficiency of companies located in the immediate neighbourhood of the regional capital. The revealed patterns characterising the heterogeneous functioning of Novosibirsk economy can be considered by regional and local authorities when making decisions to support and develop business.
{"title":"Assessment of the Impact of Agglomeration Factors on the Economic Activity: Microeconomic Analysis","authors":"E. A. Kolomak, A. I. Sherubneva","doi":"10.17059/ekon.reg.2023-3-12","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-3-12","url":null,"abstract":"While agglomeration effects are an essential element of the economic environment determining the decision-making on the capacity allocation and implementation of infrastructure projects, their impact in the East of Russia is questioned. Development conditions of Novosibirsk oblast can have a contradictory effect on agglomeration forces. The paper aims to obtain quantitative estimates of the impact of agglomeration effects on enterprise performance by analysing the SPARK-Interfax database for 2019. To this end, the visualisation of the spatial distribution of the sample data, average output and profit characteristics was performed. Additionally, the econometric analysis of the influence of agglomeration factors on enterprise performance was conducted. As a result, the microeconomic analysis showed a statistically significant impact of agglomeration effects on the productivity of firms in Novosibirsk oblast. A two-fold increase in the distance to the regional capital leads to a reduction in output and profitability of enterprises by 3.5 %. This finding supports the development and implementation of private and public infrastructure projects. The analysis demonstrated a higher differentiation of profit indicators in cities, as well as a significant drop in performance and efficiency of companies located in the immediate neighbourhood of the regional capital. The revealed patterns characterising the heterogeneous functioning of Novosibirsk economy can be considered by regional and local authorities when making decisions to support and develop business.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":"482 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135838694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.17059/ekon.reg.2023-3-21
G. S. Mukina, D. Z. Aiguzhinova, L. A. Popp
In the post-pandemic period, research on integration unions gained importance due to the increasing regionalisation. The article assesses economic development of the Eurasian Economic Union (EAEU) considering the events of 2020–2022 and examines the prospects for integration cooperation within the Union. By analysing the economic development of the EAEU countries in the context of the COVID-19 pandemic, the study aims to identify its changes and determine integration prospects. It is hypothesised that the pandemic has activated the integration cooperation mechanism of the EAEU in the trade and economic fields and clarified the prospects within the Union. Methods of economic and statistical, structural and comparative analysis were used to monitor changes in key indicators of economic development of the EAEU. Gross domestic product (GDP) of the EAEU decreased by 11.9 % in 2020; however, it has already shown an increase of 4.4 % in 2021, even though three waves of the pandemic were recorded that year. This indicator continued to grow in 2022, despite the economic sanctions against Russia and Belarus. While mutual and foreign trade declined in 2020, only these indicators significantly increased in 2021 and 2022. Among other unions, the EAEU is leading in terms of mutual trade growth in the period 2021–2022, indicating the possibility of economic success of the macroregion in this area. The study proved that the EAEU should establish a new strategy to provide mutual assistance in case of crisis. The findings contribute to the study of the economics of integration associations, and can be used to create economic development strategies for the EAEU. Future research may examine the impact of sanctions against individual members on the economic development of the EAEU.
{"title":"Economic Development of the EAEU during the COVID Pandemic and Prospects for Integration Cooperation","authors":"G. S. Mukina, D. Z. Aiguzhinova, L. A. Popp","doi":"10.17059/ekon.reg.2023-3-21","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-3-21","url":null,"abstract":"In the post-pandemic period, research on integration unions gained importance due to the increasing regionalisation. The article assesses economic development of the Eurasian Economic Union (EAEU) considering the events of 2020–2022 and examines the prospects for integration cooperation within the Union. By analysing the economic development of the EAEU countries in the context of the COVID-19 pandemic, the study aims to identify its changes and determine integration prospects. It is hypothesised that the pandemic has activated the integration cooperation mechanism of the EAEU in the trade and economic fields and clarified the prospects within the Union. Methods of economic and statistical, structural and comparative analysis were used to monitor changes in key indicators of economic development of the EAEU. Gross domestic product (GDP) of the EAEU decreased by 11.9 % in 2020; however, it has already shown an increase of 4.4 % in 2021, even though three waves of the pandemic were recorded that year. This indicator continued to grow in 2022, despite the economic sanctions against Russia and Belarus. While mutual and foreign trade declined in 2020, only these indicators significantly increased in 2021 and 2022. Among other unions, the EAEU is leading in terms of mutual trade growth in the period 2021–2022, indicating the possibility of economic success of the macroregion in this area. The study proved that the EAEU should establish a new strategy to provide mutual assistance in case of crisis. The findings contribute to the study of the economics of integration associations, and can be used to create economic development strategies for the EAEU. Future research may examine the impact of sanctions against individual members on the economic development of the EAEU.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135801848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.17059/ekon.reg.2023-3-5
E. A. Tretiakova, M. A. Kurganov
Introduction of the concept of sustainable development (SD) led to the transformation of values and interests of key stakeholders: the government, population and business. Since consideration of regional stakeholder interests is crucial for ensuring SD of large countries like Russia, a methodology is needed to assess their fulfilment, balance and consistency. However, previous studies of regional sustainable development have not yet proposed such a methodology. The present paper examined and classified regional stakeholder interests and developed an indicator framework to evaluate their fulfilment. We proposed an algorithm for calculating 9 group and 7 integral indices which were subsequently used to measure the socio-economic-environmental balance and inter-stakeholder consistency of interests. The methodology was applied to 17 regions of the Volga and Ural Federal Districts of Russia. The research discovered that sustainable development in most regions was at a medium level. There was no significant difference in the fulfilment of interests among the different stakeholders, which can be interpreted as a factor strengthening social cohesion. Additionally, a socio-economic-environmental imbalance was revealed: the fulfilment of social interests was the highest and that of environmental interests was the lowest. Regression modelling has shown that the presence of this imbalance has a negative impact on SD of Russian regions. The proposed methodology may contribute to broaden the scope of analytical research in the field of sustainable development.
{"title":"Stakeholder Approach to the Regional Sustainable Development: Empirical Study","authors":"E. A. Tretiakova, M. A. Kurganov","doi":"10.17059/ekon.reg.2023-3-5","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-3-5","url":null,"abstract":"Introduction of the concept of sustainable development (SD) led to the transformation of values and interests of key stakeholders: the government, population and business. Since consideration of regional stakeholder interests is crucial for ensuring SD of large countries like Russia, a methodology is needed to assess their fulfilment, balance and consistency. However, previous studies of regional sustainable development have not yet proposed such a methodology. The present paper examined and classified regional stakeholder interests and developed an indicator framework to evaluate their fulfilment. We proposed an algorithm for calculating 9 group and 7 integral indices which were subsequently used to measure the socio-economic-environmental balance and inter-stakeholder consistency of interests. The methodology was applied to 17 regions of the Volga and Ural Federal Districts of Russia. The research discovered that sustainable development in most regions was at a medium level. There was no significant difference in the fulfilment of interests among the different stakeholders, which can be interpreted as a factor strengthening social cohesion. Additionally, a socio-economic-environmental imbalance was revealed: the fulfilment of social interests was the highest and that of environmental interests was the lowest. Regression modelling has shown that the presence of this imbalance has a negative impact on SD of Russian regions. The proposed methodology may contribute to broaden the scope of analytical research in the field of sustainable development.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135799003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.17059/ekon.reg.2023-3-1
S. O. Mamman, K. Sohag
Structural transformation is a compelling measure of economic progress as it shifts from less productive to more productive sectors, spurred by technological improvement and digitalisation. Despite the benefits of structural transformation in fostering economic growth, it has been contended that it will exacerbate income inequality. Given the critical role of digitalisation over the years in Africa, the current study investigates the pattern and impact of structural transformation on inclusive growth. To accomplish this, we utilised both absolute (poverty) and relative (income inequality) measures of pro-poor growth for all African countries. Using quantiles via moments panel model, we showed that the structural transformation from agriculture to services reduced the incidence of poverty (extreme poverty) while increasing inequality (Gini coefficient). On the other hand, manufacturing had no significant effect on poverty or inequality, indicating the region’s slow pace of industrialisation. Using income share measures, we found evidence of inequality across and within sectors, particularly in the services sector. Finally, we observed that digitalisation and technological processes significantly reduced the incidence of extreme poverty and inequality. Hence, the study recommends that Africa capitalise on its comparative advantage in the agricultural sector by establishing investment and manufacturing zones to develop the industrial sector. Furthermore, gains in the manufacturing sector could be realised through a concerted effort to improve the industrialisation process.
{"title":"Inclusive Growth and Structural Transformation: The Role of Innovation and Digitalisation Spillover","authors":"S. O. Mamman, K. Sohag","doi":"10.17059/ekon.reg.2023-3-1","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-3-1","url":null,"abstract":"Structural transformation is a compelling measure of economic progress as it shifts from less productive to more productive sectors, spurred by technological improvement and digitalisation. Despite the benefits of structural transformation in fostering economic growth, it has been contended that it will exacerbate income inequality. Given the critical role of digitalisation over the years in Africa, the current study investigates the pattern and impact of structural transformation on inclusive growth. To accomplish this, we utilised both absolute (poverty) and relative (income inequality) measures of pro-poor growth for all African countries. Using quantiles via moments panel model, we showed that the structural transformation from agriculture to services reduced the incidence of poverty (extreme poverty) while increasing inequality (Gini coefficient). On the other hand, manufacturing had no significant effect on poverty or inequality, indicating the region’s slow pace of industrialisation. Using income share measures, we found evidence of inequality across and within sectors, particularly in the services sector. Finally, we observed that digitalisation and technological processes significantly reduced the incidence of extreme poverty and inequality. Hence, the study recommends that Africa capitalise on its comparative advantage in the agricultural sector by establishing investment and manufacturing zones to develop the industrial sector. Furthermore, gains in the manufacturing sector could be realised through a concerted effort to improve the industrialisation process.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135799191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.17059/ekon.reg.2023-3-23
E. V. Semerikova, A. O. Blokhina, A. Nastansky
Germany is characterised by heterogeneous regional development in various economic spheres, including housing markets. Differences in housing prices persist during decades, causing undesirable inequality, affecting migration and employment patterns. The purpose of this work is to identify regional factors which affect regional housing prices in Germany. The peculiarity of the study is the consideration of the spatial location of regions for analysing the influence of the characteristics of neighbouring regions. Based on data from 397 German regions for 2004-2019, spatial econometric panel data models are built, which consider both selling and rental prices. The following factors that affect demand in the housing market are used as determinants of housing prices: the unemployment rate, the balance of pendulum migration at the place of work and living, the share of employment, wages, the number of employees, gross regional product. The analysis findings revealed that factors that raise income for the population trigger an upsurge in demand and prices for housing. Conversely, opposite effects result in a decline in prices due to a decrease in demand. Moreover, it was verified that neighbouring regions mutually affect housing markets through pendulum migration and the creation of economic clusters with similar living standards and prices. Furthermore, changes in labour market metrics are crucial; unemployment, wages, and the number of workers in nearby regions have a significant influence on real estate prices in the area under examination. The study’s practical importance lies in the possibility of using its outcomes to develop regional and migration policies.
{"title":"Determinants of Regional Disparities in Housing Prices: A Spatial Analysis of German Regions","authors":"E. V. Semerikova, A. O. Blokhina, A. Nastansky","doi":"10.17059/ekon.reg.2023-3-23","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-3-23","url":null,"abstract":"Germany is characterised by heterogeneous regional development in various economic spheres, including housing markets. Differences in housing prices persist during decades, causing undesirable inequality, affecting migration and employment patterns. The purpose of this work is to identify regional factors which affect regional housing prices in Germany. The peculiarity of the study is the consideration of the spatial location of regions for analysing the influence of the characteristics of neighbouring regions. Based on data from 397 German regions for 2004-2019, spatial econometric panel data models are built, which consider both selling and rental prices. The following factors that affect demand in the housing market are used as determinants of housing prices: the unemployment rate, the balance of pendulum migration at the place of work and living, the share of employment, wages, the number of employees, gross regional product. The analysis findings revealed that factors that raise income for the population trigger an upsurge in demand and prices for housing. Conversely, opposite effects result in a decline in prices due to a decrease in demand. Moreover, it was verified that neighbouring regions mutually affect housing markets through pendulum migration and the creation of economic clusters with similar living standards and prices. Furthermore, changes in labour market metrics are crucial; unemployment, wages, and the number of workers in nearby regions have a significant influence on real estate prices in the area under examination. The study’s practical importance lies in the possibility of using its outcomes to develop regional and migration policies.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":"283 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135801855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.17059/ekon.reg.2023-3-9
O. A. Kozlova, A. A Provorova, O. V. Gubina
The development of the Russian North and Arctic requires labour resources, primarily from among local inhabitants. This goal can be achieved due to an increase in the retirement age in Russia; however, the involvement of local older population in social production is limited by health problems and low life expectancy. The study hypothesises that the extension of economic activity of older people in the northern regions is possible with an increase in their life expectancy. In order to assess the years of life lost according on the causes of death, statistical analysis of life expectancy at birth (LEB) and calculations of the eliminated reserves of mortality were performed. To this end, the research examined statistics of the Federal State Statistics Service on demographic processes in the Russian North and data of Arkhangelskstat on age-specific mortality rates of Arkhangelsk oblast, one of the regions of the Far North and areas equated to them. The obtained results indicate high rates of future years of life lost from all leading causes of death for older men. Diseases of the circulatory system and external causes of death among male population, and diseases of the circulatory system and neoplasms among female population are the main reasons for the reduction in life expectancy in Arkhangelsk oblast. The maximum reduction in mortality from diseases of the circulatory system would increase the life expectancy of the inhabitants of Arkhangelsk oblast by 6.17 years, which would help extend the economic activity of the older population. The research findings can be used to update national projects and regional programmes for the development of the healthcare system, as well as to improve the quality of life of the northern population.
{"title":"Assessment of the Demographic Reserve to Extend the Economic Activity of the Older Population in the Northern Region","authors":"O. A. Kozlova, A. A Provorova, O. V. Gubina","doi":"10.17059/ekon.reg.2023-3-9","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-3-9","url":null,"abstract":"The development of the Russian North and Arctic requires labour resources, primarily from among local inhabitants. This goal can be achieved due to an increase in the retirement age in Russia; however, the involvement of local older population in social production is limited by health problems and low life expectancy. The study hypothesises that the extension of economic activity of older people in the northern regions is possible with an increase in their life expectancy. In order to assess the years of life lost according on the causes of death, statistical analysis of life expectancy at birth (LEB) and calculations of the eliminated reserves of mortality were performed. To this end, the research examined statistics of the Federal State Statistics Service on demographic processes in the Russian North and data of Arkhangelskstat on age-specific mortality rates of Arkhangelsk oblast, one of the regions of the Far North and areas equated to them. The obtained results indicate high rates of future years of life lost from all leading causes of death for older men. Diseases of the circulatory system and external causes of death among male population, and diseases of the circulatory system and neoplasms among female population are the main reasons for the reduction in life expectancy in Arkhangelsk oblast. The maximum reduction in mortality from diseases of the circulatory system would increase the life expectancy of the inhabitants of Arkhangelsk oblast by 6.17 years, which would help extend the economic activity of the older population. The research findings can be used to update national projects and regional programmes for the development of the healthcare system, as well as to improve the quality of life of the northern population.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135838692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.17059/ekon.reg.2023-3-13
I. V. Naumov, N. L. Nikulina
The current spatial heterogeneity of the localisation of research personnel and mutual spatial influences between the main centres of its concentration and neighbouring regions in Central Russia, according to the hypothesis, lead to its further growth in these centres. The present paper assessed the localisation of research personnel using spatial autocorrelation analysis. The spatial interactions between regions were analysed by the method of Anselin, considering various systems for measuring distances. The Granger test was applied to confirm the presence of the established interactions. Additionally, the study built regression models of interregional spatial interactions, assessed the concentration of factors for the development of research personnel in Russian regions and examined relevant efficiency indicators. As a result, the following mutual spatial influences in Russia were determined: between Moscow city and Saint Petersburg, Tver, Bryansk and Vladimir oblasts; between Moscow and Ivanovo, Vladimir, Oryol oblasts and the Chuvash Republic; between Nizhny Novgorod and Tula oblasts; between Saint Petersburg and Tambov, Bryansk, Vladimir, Smolensk and Yaroslavl oblasts. Spatial interactions between the regions of the Ural, Volga and Siberian districts were not identified. This result, along with the increasing dynamics of the concentration of research and development human resources in the central regions, contributes to the deepening of spatial heterogeneity of research personnel in Russia. About 65% of all research personnel in Russia are located in 22 regions, and only 4 regions (cities of Moscow and Saint Petersburg, Moscow and Nizhny Novgorod oblasts) have spatial interactions with the neighbouring regions. 60.5% of research and development human resources are concentrated there. The findings can be used to develop mechanisms for reducing the spatial heterogeneity of the development of research personnel in Russia.
{"title":"Assessment and Modelling of Spatial Interactions in the Development of Research Personnel in Russian Regions","authors":"I. V. Naumov, N. L. Nikulina","doi":"10.17059/ekon.reg.2023-3-13","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-3-13","url":null,"abstract":"The current spatial heterogeneity of the localisation of research personnel and mutual spatial influences between the main centres of its concentration and neighbouring regions in Central Russia, according to the hypothesis, lead to its further growth in these centres. The present paper assessed the localisation of research personnel using spatial autocorrelation analysis. The spatial interactions between regions were analysed by the method of Anselin, considering various systems for measuring distances. The Granger test was applied to confirm the presence of the established interactions. Additionally, the study built regression models of interregional spatial interactions, assessed the concentration of factors for the development of research personnel in Russian regions and examined relevant efficiency indicators. As a result, the following mutual spatial influences in Russia were determined: between Moscow city and Saint Petersburg, Tver, Bryansk and Vladimir oblasts; between Moscow and Ivanovo, Vladimir, Oryol oblasts and the Chuvash Republic; between Nizhny Novgorod and Tula oblasts; between Saint Petersburg and Tambov, Bryansk, Vladimir, Smolensk and Yaroslavl oblasts. Spatial interactions between the regions of the Ural, Volga and Siberian districts were not identified. This result, along with the increasing dynamics of the concentration of research and development human resources in the central regions, contributes to the deepening of spatial heterogeneity of research personnel in Russia. About 65% of all research personnel in Russia are located in 22 regions, and only 4 regions (cities of Moscow and Saint Petersburg, Moscow and Nizhny Novgorod oblasts) have spatial interactions with the neighbouring regions. 60.5% of research and development human resources are concentrated there. The findings can be used to develop mechanisms for reducing the spatial heterogeneity of the development of research personnel in Russia.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135800847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.17059/ekon.reg.2023-3-15
O. O. Sekicki-Pavlenko
Assessment of changes in the age structure in Russia is relevant due to the increasing ageing of the population and implementation of demographic policy measures. The study aims to develop a typology of the transformation of the age structure in Russian regions. It is hypothesised that differences in the speed and direction of transformation cause the formation of various types and subtypes of age structure. Official data of the Federal State Statistics Service were analysed: “Demographic Yearbook of Russia”; “Supplement to the Demographic Yearbook of Russia”; statistical bulletins “Population of the Russian Federation by sex and age”. As a result, Russian regions were grouped based on 6 types and 18 subtypes of the transformation of the age structure. Calculation of the ageing index revealed the following 6 types of age structure: very young, young, on the eve of old age, moderately old, old, and very old. The most common are regions with moderately old age structure (38.1 %), followed by regions with old age structure (25 %) and very old age structure (19 %). Regions classified as “on the eve of old age”, “young” and “very young” together account for no more than 18 %. The ageing dynamics index was calculated to identify 18 subtypes of the transformation of the age structure. The ageing trend is observed in 80 Russian regions: slow ageing of the population is recorded in 52 constituent entities, and increased ageing — in 28 regions. The rejuvenation trend is characteristic only for 4 regions: the Republic of Tuva, Moscow oblast, Saint Petersburg and the Republic of Crimea. The obtained results can be used by public authorities to improve regional demographic policy.
{"title":"Typology of the Transformation of the Age Structure in Russian Regions","authors":"O. O. Sekicki-Pavlenko","doi":"10.17059/ekon.reg.2023-3-15","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-3-15","url":null,"abstract":"Assessment of changes in the age structure in Russia is relevant due to the increasing ageing of the population and implementation of demographic policy measures. The study aims to develop a typology of the transformation of the age structure in Russian regions. It is hypothesised that differences in the speed and direction of transformation cause the formation of various types and subtypes of age structure. Official data of the Federal State Statistics Service were analysed: “Demographic Yearbook of Russia”; “Supplement to the Demographic Yearbook of Russia”; statistical bulletins “Population of the Russian Federation by sex and age”. As a result, Russian regions were grouped based on 6 types and 18 subtypes of the transformation of the age structure. Calculation of the ageing index revealed the following 6 types of age structure: very young, young, on the eve of old age, moderately old, old, and very old. The most common are regions with moderately old age structure (38.1 %), followed by regions with old age structure (25 %) and very old age structure (19 %). Regions classified as “on the eve of old age”, “young” and “very young” together account for no more than 18 %. The ageing dynamics index was calculated to identify 18 subtypes of the transformation of the age structure. The ageing trend is observed in 80 Russian regions: slow ageing of the population is recorded in 52 constituent entities, and increased ageing — in 28 regions. The rejuvenation trend is characteristic only for 4 regions: the Republic of Tuva, Moscow oblast, Saint Petersburg and the Republic of Crimea. The obtained results can be used by public authorities to improve regional demographic policy.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135800848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.17059/ekon.reg.2023-3-4
P. Yu. Makarov, A. A. Chub
Place branding became a part of regional development processes; therefore, regional conditions could affect the place branding success. Nevertheless, studies on place branding success are mostly focused on management issues, and the role of regional conditions is yet to be revealed. In this regard, the paper aims to explore how regional economic (including social and spatial) conditions affect the results of place branding activity. We assumed that regional conditions have a certain impact on place branding activities, yielding better or worse place brands survival, which we treated as the fact of observable place brand attributes continuing to exist. To test this hypothesis, a survival analysis on brands of 15 Russian regions was performed for the period from 2010 to 2021. Using the Kaplan-Meier method, we examined the impact of seven variables on place brands survival. The obtained findings confirm the positive impact on brands survival of such variables as gross regional product (GRP) per capita, regional investment, and migration attractiveness. The following variables have a negative impact: unemployment rate, the adjacency to regions already having place brands. Additionally, place brands of regions with administrative centres in smaller cities have a better survival rate than the ones with bigger cities. Finally, the impact of change of the federal subject’s head on survival was not confirmed. Thus, the present article contributes to place branding studies by unveiling the influence of regional conditions on place branding outputs and extends the methods of place branding research by using the survival analysis.
{"title":"The Impact of Regional Economic Conditions on Place Branding Results: The Survival Analysis Approach","authors":"P. Yu. Makarov, A. A. Chub","doi":"10.17059/ekon.reg.2023-3-4","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-3-4","url":null,"abstract":"Place branding became a part of regional development processes; therefore, regional conditions could affect the place branding success. Nevertheless, studies on place branding success are mostly focused on management issues, and the role of regional conditions is yet to be revealed. In this regard, the paper aims to explore how regional economic (including social and spatial) conditions affect the results of place branding activity. We assumed that regional conditions have a certain impact on place branding activities, yielding better or worse place brands survival, which we treated as the fact of observable place brand attributes continuing to exist. To test this hypothesis, a survival analysis on brands of 15 Russian regions was performed for the period from 2010 to 2021. Using the Kaplan-Meier method, we examined the impact of seven variables on place brands survival. The obtained findings confirm the positive impact on brands survival of such variables as gross regional product (GRP) per capita, regional investment, and migration attractiveness. The following variables have a negative impact: unemployment rate, the adjacency to regions already having place brands. Additionally, place brands of regions with administrative centres in smaller cities have a better survival rate than the ones with bigger cities. Finally, the impact of change of the federal subject’s head on survival was not confirmed. Thus, the present article contributes to place branding studies by unveiling the influence of regional conditions on place branding outputs and extends the methods of place branding research by using the survival analysis.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135798685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.17059/ekon.reg.2023-3-2
V. I. Suslov, A. A. Tsyplakov, T. S. Novikova
Redistribution of resources between the private and public sectors is a key issue of state policy analysis, including at the regional level. The article examines how changes in tax rates and social transfers affect the redistribution of financial resources, fixed capital and labour. The study utilised a spatial agent-based model focused on microeconomic decisions of households and enterprises. Fixed capital depends on investment policies of private and public companies; demand and supply are balanced in the labour market for a given total labour force. Tax rates and distribution of social transfers are seen as the institutional framework for making microeconomic decisions. At the meso- and macro-levels, state policy changes affect the economic structure of regions, industries, public and private sectors. The use of capital, labour and financial resources was assessed to calculate the relative size of the public sector. Simulations of changes in transfers and taxes show opposite trends in the proportion of the sectors. At given tax rates, the expansion of social transfers reduces social inequality and causes profound structural changes in the economy due to decreased provision of public goods and increased income of recipient households. The size of the public sector in terms of the use of financial resources remains practically unchanged: its share in gross domestic product decreased from 32.2 % to 30.4 %. However, the shares of capital (by 9.9 %) and labour (by 14.7 %) noticeably declined in this sector, indicating a redistribution of capital and labour from the public to the private sector. On the contrary, tax hike leads to an increase in the main indicators characterising the share of the public sector, while most of the private sector indicators fall sharply and social inequality rises significantly.
{"title":"Redistribution of Resources between the Private and Public Sectors of the Spatial Economy: An Agent-Based Approach","authors":"V. I. Suslov, A. A. Tsyplakov, T. S. Novikova","doi":"10.17059/ekon.reg.2023-3-2","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-3-2","url":null,"abstract":"Redistribution of resources between the private and public sectors is a key issue of state policy analysis, including at the regional level. The article examines how changes in tax rates and social transfers affect the redistribution of financial resources, fixed capital and labour. The study utilised a spatial agent-based model focused on microeconomic decisions of households and enterprises. Fixed capital depends on investment policies of private and public companies; demand and supply are balanced in the labour market for a given total labour force. Tax rates and distribution of social transfers are seen as the institutional framework for making microeconomic decisions. At the meso- and macro-levels, state policy changes affect the economic structure of regions, industries, public and private sectors. The use of capital, labour and financial resources was assessed to calculate the relative size of the public sector. Simulations of changes in transfers and taxes show opposite trends in the proportion of the sectors. At given tax rates, the expansion of social transfers reduces social inequality and causes profound structural changes in the economy due to decreased provision of public goods and increased income of recipient households. The size of the public sector in terms of the use of financial resources remains practically unchanged: its share in gross domestic product decreased from 32.2 % to 30.4 %. However, the shares of capital (by 9.9 %) and labour (by 14.7 %) noticeably declined in this sector, indicating a redistribution of capital and labour from the public to the private sector. On the contrary, tax hike leads to an increase in the main indicators characterising the share of the public sector, while most of the private sector indicators fall sharply and social inequality rises significantly.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":"283 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135799194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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