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":null,"pages":null},"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}
Pub Date : 2023-01-01DOI: 10.17059/ekon.reg.2023-3-18
A. D. Stoyanov, A. S. Sakharova
The subject of the present research is the assessment of access of residents of Northern cities to energy produced from renewable energy sources (RES). The largest Arctic cities in Russia, Sweden, Norway, Finland, Denmark, the USA and Canada, located above 66 ° 33 ´ North latitude, are analysed. The importance of the study is due to the categorisation of access to RES as a fundamental good in the context of Sustainable Development Goals and fight against climate change. The work uses the index method, followed by ranking cities by the level of access to energy from RES. The following variables constitute the index: variety of operators, variety of types of energy sources, alternatives of energy sources, micro- and macro-generation support. It was found that residents of Kiruna and Tromsø have the best access to energy from renewable sources due to the support of initiatives at all levels, while Utqiagvik has the lowest indicator due to its isolation. Energy from renewable energy sources does not have a significant share in all of the cities under consideration; moreover, the market is often monopolised, which limits the choice and availability of various energy sources. Consequently, it is important to create suitable conditions for developing of RES on all levels, with the focus on micro level (as it makes ordinary people participate actively in the agenda, which is the key to support such remote areas with energy); otherwise it is unlikely to support the cities and territories of the region with energy from RES.
{"title":"Accessibility of Energy from Renewable Energy Sources for Inhabitants of Arctic Cities","authors":"A. D. Stoyanov, A. S. Sakharova","doi":"10.17059/ekon.reg.2023-3-18","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-3-18","url":null,"abstract":"The subject of the present research is the assessment of access of residents of Northern cities to energy produced from renewable energy sources (RES). The largest Arctic cities in Russia, Sweden, Norway, Finland, Denmark, the USA and Canada, located above 66 ° 33 ´ North latitude, are analysed. The importance of the study is due to the categorisation of access to RES as a fundamental good in the context of Sustainable Development Goals and fight against climate change. The work uses the index method, followed by ranking cities by the level of access to energy from RES. The following variables constitute the index: variety of operators, variety of types of energy sources, alternatives of energy sources, micro- and macro-generation support. It was found that residents of Kiruna and Tromsø have the best access to energy from renewable sources due to the support of initiatives at all levels, while Utqiagvik has the lowest indicator due to its isolation. Energy from renewable energy sources does not have a significant share in all of the cities under consideration; moreover, the market is often monopolised, which limits the choice and availability of various energy sources. Consequently, it is important to create suitable conditions for developing of RES on all levels, with the focus on micro level (as it makes ordinary people participate actively in the agenda, which is the key to support such remote areas with energy); otherwise it is unlikely to support the cities and territories of the region with energy from RES.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135801836","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.2023-3-8
E. V. Orlov
Analysis of scientific sources and strategic planning documents of Russian regions and municipalities revealed that since the adoption of the federal law No. 172-FZ “On strategic planning in the Russian Federation”, significant problems have been accumulated that require an urgent solution. The study aims to develop tools for assessing the consistency of strategic planning documents at the regional and municipal levels. The Volga Federal District was selected for testing as one of the largest sub-federal entities, since obtained findings may be applied in other regions. Information on the availability, titles, implementation periods of regional and municipal strategies and programmes was collected and classified. Indicators of difference, deviation, and variance were determined for data processing. As a result, the study demonstrated that the current system of strategic planning in many Russian regions is extremely unbalanced: set implementation periods, numbers and titles of documents significantly differ, suggesting a lack of consistency in terms of other parameters, particularly, financial ones. The introduction of proposals developed in this paper will significantly improve the strategic planning at the regional and municipal levels. Additionally, the proposed tool can be used for the legislative consolidation of the list of priority areas and nomenclature of strategic planning documents in the strategic cycle. Since the analysis can be performed without specific mathematical knowledge, state and municipal authorities can also replicate this approach to ensure the strategic development of territories.
{"title":"Assessment of the Consistency of Regional and Municipal Strategic Planning Documents","authors":"E. V. Orlov","doi":"10.17059/ekon.reg.2023-3-8","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-3-8","url":null,"abstract":"Analysis of scientific sources and strategic planning documents of Russian regions and municipalities revealed that since the adoption of the federal law No. 172-FZ “On strategic planning in the Russian Federation”, significant problems have been accumulated that require an urgent solution. The study aims to develop tools for assessing the consistency of strategic planning documents at the regional and municipal levels. The Volga Federal District was selected for testing as one of the largest sub-federal entities, since obtained findings may be applied in other regions. Information on the availability, titles, implementation periods of regional and municipal strategies and programmes was collected and classified. Indicators of difference, deviation, and variance were determined for data processing. As a result, the study demonstrated that the current system of strategic planning in many Russian regions is extremely unbalanced: set implementation periods, numbers and titles of documents significantly differ, suggesting a lack of consistency in terms of other parameters, particularly, financial ones. The introduction of proposals developed in this paper will significantly improve the strategic planning at the regional and municipal levels. Additionally, the proposed tool can be used for the legislative consolidation of the list of priority areas and nomenclature of strategic planning documents in the strategic cycle. Since the analysis can be performed without specific mathematical knowledge, state and municipal authorities can also replicate this approach to ensure the strategic development of territories.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135799002","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 : 2022-01-01DOI: 10.17059/ekon.reg.2022-4-8
T. Afanasieva, A. Kazanbieva
The present article proposes and tests a new approach to the assessment of the digital economy development in order to obtain evaluative knowledge (qualitative assessments) from quantitative indicators of the constituent entities of the Russian Federation. The distinctive features of the proposed approach are the integration of cluster analysis and qualitative assessment, as well as the use of elements of the fuzzy set theory for modelling evaluative knowledge and presenting it in linguistic form at three levels of interpretation. Three methods (K-means, BIRCH, DBSCAN), differing in terms of grouping principles, were applied to improve the quality of clustering. The most suitable method for clustering the constituent entities of the Russian Federation was automatically selected based on a proven quality metric. The developed automated methodology for qualitative assessment of digital economy was tested on 15 indicators observed over 9 years, presented on the website of the Federal State Statistics Service for 83 regions of the Russian Federation. The study identified six clusters, for which three classes of qualitative assessments were determined, characterising the problems of digital economy development by indicators, their groups and year based on the aggregation of linguistic assessments. Thus, the level of the indicator (Low, Medium, High), as well as belonging to the problem according to the group of indicators (Problem/No problem) and according to all indicators (Developed/Developing) were estimated for each region in the clusters. Analysis of qualitative estimates obtained from various regional numerical indicators showed that the most «problematic» in 2010 and in 2018 was the group of indicators «Science and Innovation». Additionally, the group of indicators «Economic Efficiency» demonstrated a negative trend in the period 2010-2018, while a positive trend was observed in the group of indicators «Information Society» and «Labour Market».
{"title":"Approach to Assessing the Digital Economy Development Based on Clustering of Russian Regions","authors":"T. Afanasieva, A. Kazanbieva","doi":"10.17059/ekon.reg.2022-4-8","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-4-8","url":null,"abstract":"The present article proposes and tests a new approach to the assessment of the digital economy development in order to obtain evaluative knowledge (qualitative assessments) from quantitative indicators of the constituent entities of the Russian Federation. The distinctive features of the proposed approach are the integration of cluster analysis and qualitative assessment, as well as the use of elements of the fuzzy set theory for modelling evaluative knowledge and presenting it in linguistic form at three levels of interpretation. Three methods (K-means, BIRCH, DBSCAN), differing in terms of grouping principles, were applied to improve the quality of clustering. The most suitable method for clustering the constituent entities of the Russian Federation was automatically selected based on a proven quality metric. The developed automated methodology for qualitative assessment of digital economy was tested on 15 indicators observed over 9 years, presented on the website of the Federal State Statistics Service for 83 regions of the Russian Federation. The study identified six clusters, for which three classes of qualitative assessments were determined, characterising the problems of digital economy development by indicators, their groups and year based on the aggregation of linguistic assessments. Thus, the level of the indicator (Low, Medium, High), as well as belonging to the problem according to the group of indicators (Problem/No problem) and according to all indicators (Developed/Developing) were estimated for each region in the clusters. Analysis of qualitative estimates obtained from various regional numerical indicators showed that the most «problematic» in 2010 and in 2018 was the group of indicators «Science and Innovation». Additionally, the group of indicators «Economic Efficiency» demonstrated a negative trend in the period 2010-2018, while a positive trend was observed in the group of indicators «Information Society» and «Labour Market».","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73803325","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 : 2022-01-01DOI: 10.17059/ekon.reg.2022-3-8
R. Manshin, E. Moiseeva
High divergence of demographic and socio-economic development significantly hinders the sustainable growth of the Russian economy. This article analyses the influence of infrastructure on population distribution and development of Russian regions. The study focuses on theoretical and practical issues related to identifying the features of infrastructure development as a factor of settlement and formation of population, considering the migration attractiveness of Russian regions. The research aimed to reveal a correlation between the regional infrastructure development and population distribution characterised by its density and net migration. To this end, we calculated the correlation between these indicators of population distribution and development indices of transport, energy, social, communal and telecommunications infrastructure. Additionally, the correlation between gross regional product and the same infrastructure development indices was estimated. The correlation analysis revealed the presence of a weak positive relationship between the regional population density, net migration, and all infrastructure development indices, except for social one. The strongest positive relationship is observed between the regional population density and the transport infrastructure development index. Good transport accessibility gives people easier access to other types of infrastructure and consequently increases the spatial connectivity and demographic potential of certain areas. Infrastructure development greatly influences not only social indicators of regional development but also economic ones, as shown by the correlation between gross regional product and development indices of transport, telecommunications and energy infrastructure. Thus, according to the conducted statistical analysis, the existing but weak relationship between infrastructure development indices and population distribution confirms the presence of a set of factors, where infrastructure is not the main one. Nevertheless, the removal of infrastructure constraints and an increase in the infrastructure quality and availability will help overcome both the demographic and economic contraction of Russia.
{"title":"Influence of Infrastructure on Population Distribution and Socio-Economic Development of Russian Regions","authors":"R. Manshin, E. Moiseeva","doi":"10.17059/ekon.reg.2022-3-8","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-3-8","url":null,"abstract":"High divergence of demographic and socio-economic development significantly hinders the sustainable growth of the Russian economy. This article analyses the influence of infrastructure on population distribution and development of Russian regions. The study focuses on theoretical and practical issues related to identifying the features of infrastructure development as a factor of settlement and formation of population, considering the migration attractiveness of Russian regions. The research aimed to reveal a correlation between the regional infrastructure development and population distribution characterised by its density and net migration. To this end, we calculated the correlation between these indicators of population distribution and development indices of transport, energy, social, communal and telecommunications infrastructure. Additionally, the correlation between gross regional product and the same infrastructure development indices was estimated. The correlation analysis revealed the presence of a weak positive relationship between the regional population density, net migration, and all infrastructure development indices, except for social one. The strongest positive relationship is observed between the regional population density and the transport infrastructure development index. Good transport accessibility gives people easier access to other types of infrastructure and consequently increases the spatial connectivity and demographic potential of certain areas. Infrastructure development greatly influences not only social indicators of regional development but also economic ones, as shown by the correlation between gross regional product and development indices of transport, telecommunications and energy infrastructure. Thus, according to the conducted statistical analysis, the existing but weak relationship between infrastructure development indices and population distribution confirms the presence of a set of factors, where infrastructure is not the main one. Nevertheless, the removal of infrastructure constraints and an increase in the infrastructure quality and availability will help overcome both the demographic and economic contraction of Russia.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73079960","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 : 2022-01-01DOI: 10.17059/ekon.reg.2022-2-3
I. Savin, N. Teplyakov
Over the past decades, the process of knowledge generation has accelerated, producing a lot of scientific publications, which makes reviewing even a relatively narrow subject area very demanding, if not impossible. However, recent text data mining tools can assist researchers in conducting such analysis in an objective and time-efficient way. We conduct such a literature review on 1307 articles published in the journal Economy of Regions from 2010 to 2021 using advanced topic modelling techniques. This analysis aims to describe the main research areas in the journal over time, the dynamics of their popularity and the relationship with key quantitative indicators. We identified 22 topics ranging from “Agriculture” and “Economic Geography” to “Fiscal Policy” and “Entrepreneurship”. We estimate how popularity of these topics was changing over time and find topics that gained the most popularity from 2010 to 2021 (+17.61 %, “Spatial Economics”) or lost it (-14.58 %, “Economics of Innovation”). The topic of environmental economics collects the largest number of citations per article (3.64, on average), and the topics on monetary policy and poverty are the most popular among manuscripts in English, which is also true for articles written by authors with foreign affiliation. Papers with third-party funding are concentrated the most in “Spatial Economics” (around 11 %), and the least — in “Agriculture”. Our results can help to understand the evolution in scope of research of Economy of Regions and serve researchers to find promising directions for future studies.
{"title":"Using Computational Linguistics to Analyse Main Research Directions in Economy of Regions","authors":"I. Savin, N. Teplyakov","doi":"10.17059/ekon.reg.2022-2-3","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-2-3","url":null,"abstract":"Over the past decades, the process of knowledge generation has accelerated, producing a lot of scientific publications, which makes reviewing even a relatively narrow subject area very demanding, if not impossible. However, recent text data mining tools can assist researchers in conducting such analysis in an objective and time-efficient way. We conduct such a literature review on 1307 articles published in the journal Economy of Regions from 2010 to 2021 using advanced topic modelling techniques. This analysis aims to describe the main research areas in the journal over time, the dynamics of their popularity and the relationship with key quantitative indicators. We identified 22 topics ranging from “Agriculture” and “Economic Geography” to “Fiscal Policy” and “Entrepreneurship”. We estimate how popularity of these topics was changing over time and find topics that gained the most popularity from 2010 to 2021 (+17.61 %, “Spatial Economics”) or lost it (-14.58 %, “Economics of Innovation”). The topic of environmental economics collects the largest number of citations per article (3.64, on average), and the topics on monetary policy and poverty are the most popular among manuscripts in English, which is also true for articles written by authors with foreign affiliation. Papers with third-party funding are concentrated the most in “Spatial Economics” (around 11 %), and the least — in “Agriculture”. Our results can help to understand the evolution in scope of research of Economy of Regions and serve researchers to find promising directions for future studies.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78180286","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 : 2022-01-01DOI: 10.17059/ekon.reg.2022-4-12
A. E. Sudakova, D. Sandler
In the context of competition for resources, the higher education is characterised by the monopolisation of the system. The present study addresses the question of the applicability of the term monopolisation to the education system as a socially significant sector. The concept of institutional monopoly is understood as the establishment of control not by a specific university or a group of universities, but by their founder acting in the interests of the state. The article reveals specific features of institutional monopoly. Using the proposed methodological tools, the study examines resource allocation and the manifestation of elements of institutional monopoly in the higher education system. The calculations were conducted for universities subordinate to the Ministry of Education and Science and the Government of the Russian Federation. Thus, two principles of financing the higher education system of the Russian Federation can be distinguished: equalising principle (investing in the public good in order to preserve regional universities and reduce the outflow of youth) and differentiating principle (increasing the qualitative and positional characteristics of the best performing universities). In some areas, the system has signs of oligopoly. For example, 4 universities occupy 43 % of the market in terms of the concentration of talented students, and the calculated Lind index showed that only 3 universities are the main market players. However, with regard to financial resources, the higher education system of the Russian Federation can be described as low-concentrated. Thus, elements of institutional monopoly are present in the Russian higher education system. Simultaneously, there are two types of universities receiving resources: (1) leaders capable of creating and maintaining productive organisations (rent contributes to the formation of positional characteristics of universities); (2) less competitive universities playing an important role in preserving regional human capital by reducing the outflow of youth due to educational migration (rent is an investment in education as a public good).
{"title":"Institutional Monopoly of the Higher Education System: National and Regional Level","authors":"A. E. Sudakova, D. Sandler","doi":"10.17059/ekon.reg.2022-4-12","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-4-12","url":null,"abstract":"In the context of competition for resources, the higher education is characterised by the monopolisation of the system. The present study addresses the question of the applicability of the term monopolisation to the education system as a socially significant sector. The concept of institutional monopoly is understood as the establishment of control not by a specific university or a group of universities, but by their founder acting in the interests of the state. The article reveals specific features of institutional monopoly. Using the proposed methodological tools, the study examines resource allocation and the manifestation of elements of institutional monopoly in the higher education system. The calculations were conducted for universities subordinate to the Ministry of Education and Science and the Government of the Russian Federation. Thus, two principles of financing the higher education system of the Russian Federation can be distinguished: equalising principle (investing in the public good in order to preserve regional universities and reduce the outflow of youth) and differentiating principle (increasing the qualitative and positional characteristics of the best performing universities). In some areas, the system has signs of oligopoly. For example, 4 universities occupy 43 % of the market in terms of the concentration of talented students, and the calculated Lind index showed that only 3 universities are the main market players. However, with regard to financial resources, the higher education system of the Russian Federation can be described as low-concentrated. Thus, elements of institutional monopoly are present in the Russian higher education system. Simultaneously, there are two types of universities receiving resources: (1) leaders capable of creating and maintaining productive organisations (rent contributes to the formation of positional characteristics of universities); (2) less competitive universities playing an important role in preserving regional human capital by reducing the outflow of youth due to educational migration (rent is an investment in education as a public good).","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79498028","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 : 2022-01-01DOI: 10.17059/ekon.reg.2022-3-14
I. Naumov, N. Nikulina
Uneven socio-economic development of municipalities in various regions depends on many factors, in particular, on the peculiarities of the distribution of economic entities and their activities. We hypothesise that this heterogeneity increases due to unequal distribution of labour and investment resources. In order to test this hypothesis, the study assesses the impact of the distribution of personnel and investment resources in the municipalities of Sverdlovsk oblast on the spatial heterogeneity of economic activity. To this end, the methods of regression and spatial autocorrelation analysis were used. The developed methodology involves assessing the spatial heterogeneity of economic activities of various enterprises in territorial systems. Spatial regression analysis was applied to examine the impact of labour and investment resources on the heterogeneity dynamics, while spatial autocorrelation analysis was used to consider the distribution of these factors. Due to the systematic use of spatial autocorrelation analysis for various spatial weights matrices, as well as regression analysis based on panel data and geographically weighted regression, the degree of the influence of factors on the heterogeneity of economic activities in certain municipalities was established. Testing of the presented methodology revealed a trend towards an increase in the spatial heterogeneity of economic activity, its concentration in Ekaterinburg, Nizhny Tagil, Kamensk-Uralsky, as well as in Verkhnyaya Pyshma, Pervouralsk, Verkhnesaldinsky, Polevskoy, Revda, Kachkanarsky, Berezovsky, Zarechny and Serovsky urban okrugs in the period from 2017 to 2020. The Cobb-Douglas model showed that the main factor contributing to the increase in the spatial heterogeneity of the economic entity activity is labour costs; the volume of attracted investments plays an important role in municipalities with a high concentration of shipped goods and rendered services. Based on the model modified using geographically weighted regression, the study established a degree of spatial influence of the examined factors on the economic activity and, together with a spatial autocorrelation analysis of the distribution of human resources and investments in the municipalities of the region, to confirm the hypothesis put forward.
{"title":"Assessment of the Spatial Heterogeneity of Economic Activity in the Municipalities of Sverdlovsk Oblast","authors":"I. Naumov, N. Nikulina","doi":"10.17059/ekon.reg.2022-3-14","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-3-14","url":null,"abstract":"Uneven socio-economic development of municipalities in various regions depends on many factors, in particular, on the peculiarities of the distribution of economic entities and their activities. We hypothesise that this heterogeneity increases due to unequal distribution of labour and investment resources. In order to test this hypothesis, the study assesses the impact of the distribution of personnel and investment resources in the municipalities of Sverdlovsk oblast on the spatial heterogeneity of economic activity. To this end, the methods of regression and spatial autocorrelation analysis were used. The developed methodology involves assessing the spatial heterogeneity of economic activities of various enterprises in territorial systems. Spatial regression analysis was applied to examine the impact of labour and investment resources on the heterogeneity dynamics, while spatial autocorrelation analysis was used to consider the distribution of these factors. Due to the systematic use of spatial autocorrelation analysis for various spatial weights matrices, as well as regression analysis based on panel data and geographically weighted regression, the degree of the influence of factors on the heterogeneity of economic activities in certain municipalities was established. Testing of the presented methodology revealed a trend towards an increase in the spatial heterogeneity of economic activity, its concentration in Ekaterinburg, Nizhny Tagil, Kamensk-Uralsky, as well as in Verkhnyaya Pyshma, Pervouralsk, Verkhnesaldinsky, Polevskoy, Revda, Kachkanarsky, Berezovsky, Zarechny and Serovsky urban okrugs in the period from 2017 to 2020. The Cobb-Douglas model showed that the main factor contributing to the increase in the spatial heterogeneity of the economic entity activity is labour costs; the volume of attracted investments plays an important role in municipalities with a high concentration of shipped goods and rendered services. Based on the model modified using geographically weighted regression, the study established a degree of spatial influence of the examined factors on the economic activity and, together with a spatial autocorrelation analysis of the distribution of human resources and investments in the municipalities of the region, to confirm the hypothesis put forward.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84836297","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 : 2022-01-01DOI: 10.17059/ekon.reg.2022-2-2
S. Rastvortseva
The concentration of organisations in a city or region allows companies to receive benefits without additional costs and increase their productivity. It has been empirically proven that urbanisation and localisation effects of agglomerations contribute to economic growth and development, and therefore should be taken into account in regional and urban policies. The article considers the factors of agglomeration formation, their specific development and impact on the economy of regions and cities. The paper examines studies on the territorial distribution of companies and the population, including creative capital, showing the connection with innovative systems and knowledge capital. The research demonstrates how international trade, market competition, the transport system development and many other factors affect agglomerations. The study of agglomeration processes intersects with other fields of science, such as evolutionary economics, cluster organisation, specialisation and diversification, demography of firms. To cover the topic, works in the field of agglomeration processes were systematised by using time-domain, terminological and geographical analysis, as well by studying definitions and typology, based on data obtained from Google Scholar and Web of Science for 1959–2018. It is revealed that agglomerations are considered in such scientific fields as economics, geography, regional urban planning, urban studies, management and regional studies. The key terms are agglomeration economy (economics), localisation, urbanisation, agglomeration forces, agglomerative and deglomerative factors. These works are geographically distributed, and most of them are conducted in the USA (mainly at the University of California), Great Britain (London School of Economics and Law) and China (Chinese Academy of Sciences and Peking University). The presented research review will serve as a starting point for a more in-depth study of agglomeration processes in various fields of economics.
组织集中在一个城市或地区,可以使公司在没有额外成本的情况下获得利益,并提高生产率。实证证明,城市群的城市化和地方化效应有助于经济增长和发展,因此应在区域和城市政策中予以考虑。本文研究了城市群形成的因素、具体发展及其对区域和城市经济的影响。本文考察了企业和人口(包括创造性资本)的地域分布,揭示了创新系统和知识资本之间的联系。研究表明,国际贸易、市场竞争、交通运输系统的发展和许多其他因素如何影响集聚。集聚过程的研究与其他科学领域交叉,如进化经济学、集群组织、专业化和多样化、企业人口统计学。为了涵盖这一主题,基于Google Scholar和Web of Science获得的1959-2018年的数据,通过时域、术语和地理分析,以及研究定义和类型学,对集聚过程领域的工作进行了系统化。研究发现,经济、地理、区域城市规划、城市研究、管理学和区域研究等科学领域都在考虑城市群。关键术语是集聚经济(经济学)、地方化、城市化、集聚力量、集聚和去集聚因素。这些研究工作是地理分布的,大部分是在美国(主要是在加州大学)、英国(伦敦政法学院)和中国(中国科学院和北京大学)进行的。本文的研究综述将为更深入地研究经济学各个领域的集聚过程提供一个起点。
{"title":"An Overview of Investigations Concerning Agglomerations in Regional Economy","authors":"S. Rastvortseva","doi":"10.17059/ekon.reg.2022-2-2","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-2-2","url":null,"abstract":"The concentration of organisations in a city or region allows companies to receive benefits without additional costs and increase their productivity. It has been empirically proven that urbanisation and localisation effects of agglomerations contribute to economic growth and development, and therefore should be taken into account in regional and urban policies. The article considers the factors of agglomeration formation, their specific development and impact on the economy of regions and cities. The paper examines studies on the territorial distribution of companies and the population, including creative capital, showing the connection with innovative systems and knowledge capital. The research demonstrates how international trade, market competition, the transport system development and many other factors affect agglomerations. The study of agglomeration processes intersects with other fields of science, such as evolutionary economics, cluster organisation, specialisation and diversification, demography of firms. To cover the topic, works in the field of agglomeration processes were systematised by using time-domain, terminological and geographical analysis, as well by studying definitions and typology, based on data obtained from Google Scholar and Web of Science for 1959–2018. It is revealed that agglomerations are considered in such scientific fields as economics, geography, regional urban planning, urban studies, management and regional studies. The key terms are agglomeration economy (economics), localisation, urbanisation, agglomeration forces, agglomerative and deglomerative factors. These works are geographically distributed, and most of them are conducted in the USA (mainly at the University of California), Great Britain (London School of Economics and Law) and China (Chinese Academy of Sciences and Peking University). The presented research review will serve as a starting point for a more in-depth study of agglomeration processes in various fields of economics.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87114292","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 : 2022-01-01DOI: 10.17059/ekon.reg.2022-4-16
E. Chernova, S. Razmanova
Since the beginning of 2021, world energy prices have been rapidly increasing, reaching such a high level that entire industries, small and medium-sized enterprises became uncompetitive, while retail electricity consumers became insolvent. The European Union energy policy, now focused on the development of alternative energy sources, contributed to a decline in profitability of fossil fuel used for electricity generation. The present paper examines the roots of the current economic crisis in the European market and opportunities to overcome it. To this end, the following objectives were set: to assess existing and alternative gas supply to the European market, to consider the link between existing gas contracts and spot prices. According to the conducted analysis, the lack of new liquefied natural gas (LNG) facilities due to a decrease in investment in the context of energy price reduction and the COVID-19 spread is the main constraint to the expansion of alternative gas supply to Europe in the medium term (2022–2030). The study revealed that a sharp transition of industries and households to the use of renewable energy sources has become one of the reasons for current crisis. Electricity generation from renewables nowadays cannot catch up with the demand for energy that can be produced by coal, gas and nuclear power plants. Further research directions include assessment of the probability of a transition from the seller’s market to the buyer’s market.
{"title":"Gas Crisis in the European Commodity Market: Roots and Opportunities to Overcome","authors":"E. Chernova, S. Razmanova","doi":"10.17059/ekon.reg.2022-4-16","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-4-16","url":null,"abstract":"Since the beginning of 2021, world energy prices have been rapidly increasing, reaching such a high level that entire industries, small and medium-sized enterprises became uncompetitive, while retail electricity consumers became insolvent. The European Union energy policy, now focused on the development of alternative energy sources, contributed to a decline in profitability of fossil fuel used for electricity generation. The present paper examines the roots of the current economic crisis in the European market and opportunities to overcome it. To this end, the following objectives were set: to assess existing and alternative gas supply to the European market, to consider the link between existing gas contracts and spot prices. According to the conducted analysis, the lack of new liquefied natural gas (LNG) facilities due to a decrease in investment in the context of energy price reduction and the COVID-19 spread is the main constraint to the expansion of alternative gas supply to Europe in the medium term (2022–2030). The study revealed that a sharp transition of industries and households to the use of renewable energy sources has become one of the reasons for current crisis. Electricity generation from renewables nowadays cannot catch up with the demand for energy that can be produced by coal, gas and nuclear power plants. Further research directions include assessment of the probability of a transition from the seller’s market to the buyer’s market.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83504677","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}