Pub Date : 2023-01-01DOI: 10.17059/ekon.reg.2023-2-18
L. Agheli, Levin, P. Im
The overall economic performance is summarised in the economic growth. It occurs when resources are combined technically in an effective way. While advanced countries have no reliance on natural resources, they experience steady growth compared to natural resource-abundant countries. The Caspian Sea basin countries (Azerbaijan, Iran, Kazakhstan, Russia, and Turkmenistan) and Central Asia states (Kyrgyz Republic, Tajikistan, and Uzbekistan) own considerable mineral and ecological resources. This paper aims to examine the relationship between economic growth and natural resource depletion in the region during 1997–2019. Due to abundance of natural resources, this region trades fossil fuels and minerals with other economic blocs. Hence, foreign direct investment is added into the regression model in order to account for economic openness. In addition, the share of industry value added in gross domestic product is included to embody the industrialisation impact on economic growth. Finally, the tertiary enrolment is entered into the regression to measure the effect of human capital on economic growth. After specifying the econometric model, variables under study were tested for unit root. Due to difference in order of integration among variables, panel fully modified least squares method was used to estimate the model. The estimation results indicate the significant and positive effects of natural resource depletion, foreign direct investment, the share of industry value added and tertiary enrolment on economic growth. These findings imply that natural resource depletion contributes to economic growth much greater than foreign direct investment and tertiary enrolment. Thus, the resource curse is not confirmed across the examined countries.
{"title":"The Nexus between Economic Growth, Natural Resource Depletion and Foreign Direct Investment","authors":"L. Agheli, Levin, P. Im","doi":"10.17059/ekon.reg.2023-2-18","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-2-18","url":null,"abstract":"The overall economic performance is summarised in the economic growth. It occurs when resources are combined technically in an effective way. While advanced countries have no reliance on natural resources, they experience steady growth compared to natural resource-abundant countries. The Caspian Sea basin countries (Azerbaijan, Iran, Kazakhstan, Russia, and Turkmenistan) and Central Asia states (Kyrgyz Republic, Tajikistan, and Uzbekistan) own considerable mineral and ecological resources. This paper aims to examine the relationship between economic growth and natural resource depletion in the region during 1997–2019. Due to abundance of natural resources, this region trades fossil fuels and minerals with other economic blocs. Hence, foreign direct investment is added into the regression model in order to account for economic openness. In addition, the share of industry value added in gross domestic product is included to embody the industrialisation impact on economic growth. Finally, the tertiary enrolment is entered into the regression to measure the effect of human capital on economic growth. After specifying the econometric model, variables under study were tested for unit root. Due to difference in order of integration among variables, panel fully modified least squares method was used to estimate the model. The estimation results indicate the significant and positive effects of natural resource depletion, foreign direct investment, the share of industry value added and tertiary enrolment on economic growth. These findings imply that natural resource depletion contributes to economic growth much greater than foreign direct investment and tertiary enrolment. Thus, the resource curse is not confirmed across the examined countries.","PeriodicalId":47897,"journal":{"name":"Cambridge Journal of Regions Economy and Society","volume":"42 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79116204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","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.2023-1-14
R. Shestakov, E. I. Lovchikova
The diversity of natural, climatic, and economic conditions of Russian regions implies a wide range of approaches to their classification. Simultaneously, the task of creating an abstract methodology for any branch of the national economy becomes more complicated. Effective clustering plays an important role in the establishment and implementation of agricultural and economic policies. The paper explores the potential of basic agricultural and economic regional clustering based on time series of main eco-nomic and agricultural development indicators. The dynamic segmentation technique was applied in order to monitor and predict the direction of meso-economic changes. Official Russian statistics were analysed to identify groups of indicators on production, production and institutional, and production and structural criteria. The k-means clustering algorithm was chosen as the key research method. Based on the three simulated regional segments, baseline average values were calculated. Then, the segments were classified according to the obtained characteristics. The outliers, significantly differing from the main data sets, were considered separately. The findings confirmed a wide spatial distribution of regions included in certain agricultural and economic segments. The presented classification can be applied to justify the directions and choice of instruments of agricultural and economic policy and a strategy for creating production clusters. Moreover, it can be used to plan the activities of regional agri-businesses and reduce their devel-opment imbalances. To improve the dynamic segmentation technique in the field of agricultural and economic development, the analysis can be expanded by changing the examined time interval, increasing the number of factors included in the model and their interactions, and introducing new clustering algorithms. Additionally, this model can be used to forecast structural changes and production dynamics.
{"title":"Clustering of Regions Using Basic Agricultural and Economic Criteria","authors":"R. Shestakov, E. I. Lovchikova","doi":"10.17059/ekon.reg.2023-1-14","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-1-14","url":null,"abstract":"The diversity of natural, climatic, and economic conditions of Russian regions implies a wide range of approaches to their classification. Simultaneously, the task of creating an abstract methodology for any branch of the national economy becomes more complicated. Effective clustering plays an important role in the establishment and implementation of agricultural and economic policies. The paper explores the potential of basic agricultural and economic regional clustering based on time series of main eco-nomic and agricultural development indicators. The dynamic segmentation technique was applied in order to monitor and predict the direction of meso-economic changes. Official Russian statistics were analysed to identify groups of indicators on production, production and institutional, and production and structural criteria. The k-means clustering algorithm was chosen as the key research method. Based on the three simulated regional segments, baseline average values were calculated. Then, the segments were classified according to the obtained characteristics. The outliers, significantly differing from the main data sets, were considered separately. The findings confirmed a wide spatial distribution of regions included in certain agricultural and economic segments. The presented classification can be applied to justify the directions and choice of instruments of agricultural and economic policy and a strategy for creating production clusters. Moreover, it can be used to plan the activities of regional agri-businesses and reduce their devel-opment imbalances. To improve the dynamic segmentation technique in the field of agricultural and economic development, the analysis can be expanded by changing the examined time interval, increasing the number of factors included in the model and their interactions, and introducing new clustering algorithms. Additionally, this model can be used to forecast structural changes and production dynamics.","PeriodicalId":47897,"journal":{"name":"Cambridge Journal of Regions Economy and Society","volume":"58 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79780779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","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.2023-1-7
A. V. Topilin, O. D. Vorobyova
The imbalance between labour supply and demand, both by types of economic activity and by professional groups, differs in Russian regional labour markets, causing long-term unemployment and im-poverishment of the population. The article examines the transformation of the labour market, regional characteristics of market failures and its recovery during the COVID-19 pandemic. Based on sample surveys of the labour force conducted by the Federal State Statistics Service, we determined monthly unemploy-ment dynamics and, subsequently, the vulnerability and instability of regional labour markets. It is hypoth-esised that the stronger the contraction of employment and the greater the unemployment, the longer the process of labour market recovery during the pandemic; regions recover from the crisis at different speeds. Indicators of the intensity of labour market failures and its recovery are proposed. Since the pandemic is a peculiar phenomenon that affected the economy and society, human behaviour in the labour market, the concept of excessive unemployment was used (the difference between actual unemployment and its pre-pandemic level). We performed a correlation analysis of the relations between labour market failures and its recovery in four groups of regions characterised by different labour market fluctuations. The cal-culated Spearman’s coefficients showed a positive relationship between the indicators. The depth of la-bour market failures and its recovery rate in regions with developed infrastructure, attracting labour mi-grants, are revealed. A positive relationship was established between the unemployment dynamics and the increase in vacancy rate reported by employers to employment agencies, increase in the average monthly salary. This article presents the results of the first research stage. Further studies will expand the time se-ries of employment and unemployment in order to identify long-term trends and build a forecasting model.
{"title":"Dynamics and Regional Features of Labour Market Recovery During COVID-19","authors":"A. V. Topilin, O. D. Vorobyova","doi":"10.17059/ekon.reg.2023-1-7","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-1-7","url":null,"abstract":"The imbalance between labour supply and demand, both by types of economic activity and by professional groups, differs in Russian regional labour markets, causing long-term unemployment and im-poverishment of the population. The article examines the transformation of the labour market, regional characteristics of market failures and its recovery during the COVID-19 pandemic. Based on sample surveys of the labour force conducted by the Federal State Statistics Service, we determined monthly unemploy-ment dynamics and, subsequently, the vulnerability and instability of regional labour markets. It is hypoth-esised that the stronger the contraction of employment and the greater the unemployment, the longer the process of labour market recovery during the pandemic; regions recover from the crisis at different speeds. Indicators of the intensity of labour market failures and its recovery are proposed. Since the pandemic is a peculiar phenomenon that affected the economy and society, human behaviour in the labour market, the concept of excessive unemployment was used (the difference between actual unemployment and its pre-pandemic level). We performed a correlation analysis of the relations between labour market failures and its recovery in four groups of regions characterised by different labour market fluctuations. The cal-culated Spearman’s coefficients showed a positive relationship between the indicators. The depth of la-bour market failures and its recovery rate in regions with developed infrastructure, attracting labour mi-grants, are revealed. A positive relationship was established between the unemployment dynamics and the increase in vacancy rate reported by employers to employment agencies, increase in the average monthly salary. This article presents the results of the first research stage. Further studies will expand the time se-ries of employment and unemployment in order to identify long-term trends and build a forecasting model.","PeriodicalId":47897,"journal":{"name":"Cambridge Journal of Regions Economy and Society","volume":"27 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86455685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","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.2023-1-5
G. Korovin
Technological and organisational opportunities provided by digitalisation to the society and economy can help improve the efficiency of industry and advance the development of industrial regions. The study aims to assess the digitalisation level and rate of industrial regions in comparison with the av-erage Russian level. For this purpose, structural and dynamic analysis, as well as the method of grouping of various indicators from the official Russian statistics in the field of ICT were applied. It was hypothe-sised and confirmed that digital technologies are used more intensively in industrial regions. In terms of the use of basic information technologies, the values are higher by 1-7 %. Organisations in industrial re-gions are 3 % more likely to use global networks to interact with counterparts. There are also more en-terprises (by 4 %) that have implemented automated data exchange with partners. Industrial regions have been using special design, production management and product lifecycle software 15 % more often since 2018. However, a hypothesis of a larger-scale implementation of advanced digital technologies in indus-trial regions has not been unequivocally confirmed. The values are higher only for indicators of the use of industrial robots (by 25 %), artificial intelligence technologies (by 12.4 %), digital platforms (by 3.4 %), geo-information systems (by 4.7 %), the Internet of Things (by 4.3 %). The findings can be used to develop digi-talisation strategies at the regional and federal levels. Variability of the regulatory framework for collecting statistics and underdeveloped terminology in the field of digital technologies can be considered as limita-tions to the application of the results. Further research may focus on building econometric and other models for implementing digitalisation in regions.
{"title":"Comparative Assessment of Digitalisation in Russian Industrial Regions","authors":"G. Korovin","doi":"10.17059/ekon.reg.2023-1-5","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-1-5","url":null,"abstract":"Technological and organisational opportunities provided by digitalisation to the society and economy can help improve the efficiency of industry and advance the development of industrial regions. The study aims to assess the digitalisation level and rate of industrial regions in comparison with the av-erage Russian level. For this purpose, structural and dynamic analysis, as well as the method of grouping of various indicators from the official Russian statistics in the field of ICT were applied. It was hypothe-sised and confirmed that digital technologies are used more intensively in industrial regions. In terms of the use of basic information technologies, the values are higher by 1-7 %. Organisations in industrial re-gions are 3 % more likely to use global networks to interact with counterparts. There are also more en-terprises (by 4 %) that have implemented automated data exchange with partners. Industrial regions have been using special design, production management and product lifecycle software 15 % more often since 2018. However, a hypothesis of a larger-scale implementation of advanced digital technologies in indus-trial regions has not been unequivocally confirmed. The values are higher only for indicators of the use of industrial robots (by 25 %), artificial intelligence technologies (by 12.4 %), digital platforms (by 3.4 %), geo-information systems (by 4.7 %), the Internet of Things (by 4.3 %). The findings can be used to develop digi-talisation strategies at the regional and federal levels. Variability of the regulatory framework for collecting statistics and underdeveloped terminology in the field of digital technologies can be considered as limita-tions to the application of the results. Further research may focus on building econometric and other models for implementing digitalisation in regions.","PeriodicalId":47897,"journal":{"name":"Cambridge Journal of Regions Economy and Society","volume":"11 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75072895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","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.2023-2-11
. Н.Н.КуницынаiD, А. В. Д. I. С. Ф. университет, Российская Ставрополь, Федерация, СОЦиА льНОе РАЗВитие РеГиОНА, . NataliaN.KunitsynaiD, Aleksandr V. Dzhioev
The coronavirus spread transformed the economy and social order, and dealt a crushing blow to the labour market. Considering the worsening unemployment, it becomes important to reduce informal employment, which leads to an increase in the shadow economy. It is hypothesised that the decline in official income is accompanied by an increase in informal employment differentiated across Russian region. The study aims to theoretically justify and empirically confirm the relationship between the consequences of the pandemic, decline in population income and dynamics of informal employment in regions, as well as to develop ways to reduce their negative impact on the labour market. The study utilised an approach of the Federal State Statistics Service (Rosstat) to determining employment criteria; additionally, expert and analytical methods, analysis of statistical series, clustering and cartography were applied. The regions were clustered according to Ward’s hierarchical method based on weighted standardised data. To this end, official data from Rosstat, the United Nations, and the World Bank were examined. As a result, the analysis of informal employment in Russian regions during the pandemic did not confirm the hypothesis, showing that informal employment actually decreased in most constituent entities; the largest decrease was observed in the North Caucasus republics. The performed clustering revealed groups of Russian regions in terms of the dependence of informal employment on average per capita income and gross regional product per capita. The obtained findings can be used to develop standard solutions for establishing long- and short-term support measures for employees at the national, regional and micro-level aimed at reducing the negative impact of the identified reasons for the growth of informal employment.
{"title":"Dependence of Informal Employment on Population Income in Russian Regions: Lessons from the Pandemic","authors":". Н.Н.КуницынаiD, А. В. Д. I. С. Ф. университет, Российская Ставрополь, Федерация, СОЦиА льНОе РАЗВитие РеГиОНА, . NataliaN.KunitsynaiD, Aleksandr V. Dzhioev","doi":"10.17059/ekon.reg.2023-2-11","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-2-11","url":null,"abstract":"The coronavirus spread transformed the economy and social order, and dealt a crushing blow to the labour market. Considering the worsening unemployment, it becomes important to reduce informal employment, which leads to an increase in the shadow economy. It is hypothesised that the decline in official income is accompanied by an increase in informal employment differentiated across Russian region. The study aims to theoretically justify and empirically confirm the relationship between the consequences of the pandemic, decline in population income and dynamics of informal employment in regions, as well as to develop ways to reduce their negative impact on the labour market. The study utilised an approach of the Federal State Statistics Service (Rosstat) to determining employment criteria; additionally, expert and analytical methods, analysis of statistical series, clustering and cartography were applied. The regions were clustered according to Ward’s hierarchical method based on weighted standardised data. To this end, official data from Rosstat, the United Nations, and the World Bank were examined. As a result, the analysis of informal employment in Russian regions during the pandemic did not confirm the hypothesis, showing that informal employment actually decreased in most constituent entities; the largest decrease was observed in the North Caucasus republics. The performed clustering revealed groups of Russian regions in terms of the dependence of informal employment on average per capita income and gross regional product per capita. The obtained findings can be used to develop standard solutions for establishing long- and short-term support measures for employees at the national, regional and micro-level aimed at reducing the negative impact of the identified reasons for the growth of informal employment.","PeriodicalId":47897,"journal":{"name":"Cambridge Journal of Regions Economy and Society","volume":"57 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90587158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","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.2023-2-17
E. Piskun, K. B. Brusnikin
Analysis of statistics at the micro-level shows that the development trends of a large number of resident entrepreneurial structures of industrial parks are characterised by adverse dynamics. Accordingly, assessment of the performance of entrepreneurial structures and improvement of their management models in the general system of industrial parks become more relevant. This paper presents a methodological approach to the construction of a spatial-rating assessment of the performance of entrepreneurial structures in the system of industrial parks functioning. As a result, two groups of Russian regions were identified, among which a potential resident, when making a decision on the placement of production facilities, can choose a region taking into account its investment attractiveness and industrial activity. Two discriminant groups of industrial parks were determined, the condition of which can be defined as economically inefficient and efficient, by evaluating parks with low and high values of the park rating level in terms of attractiveness for external investors and resident entrepreneurial structures. The proposed methodological approach can be applied to improve the quality of decisions on the formation of differentiated strategies for sustainable development of both individual entrepreneurial structures in the system of industrial parks and their clusters, and regions as a whole. It is recommended for both enterprises and industrial parks when making decisions on the formation of strategies and development scenarios, as well as for federal and regional authorities when designing documents for the territorial development on the strategic and tactical level.
{"title":"Spatial-Rating Assessment of Entrepreneurial Performance in Industrial Parks of Russian Regions","authors":"E. Piskun, K. B. Brusnikin","doi":"10.17059/ekon.reg.2023-2-17","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-2-17","url":null,"abstract":"Analysis of statistics at the micro-level shows that the development trends of a large number of resident entrepreneurial structures of industrial parks are characterised by adverse dynamics. Accordingly, assessment of the performance of entrepreneurial structures and improvement of their management models in the general system of industrial parks become more relevant. This paper presents a methodological approach to the construction of a spatial-rating assessment of the performance of entrepreneurial structures in the system of industrial parks functioning. As a result, two groups of Russian regions were identified, among which a potential resident, when making a decision on the placement of production facilities, can choose a region taking into account its investment attractiveness and industrial activity. Two discriminant groups of industrial parks were determined, the condition of which can be defined as economically inefficient and efficient, by evaluating parks with low and high values of the park rating level in terms of attractiveness for external investors and resident entrepreneurial structures. The proposed methodological approach can be applied to improve the quality of decisions on the formation of differentiated strategies for sustainable development of both individual entrepreneurial structures in the system of industrial parks and their clusters, and regions as a whole. It is recommended for both enterprises and industrial parks when making decisions on the formation of strategies and development scenarios, as well as for federal and regional authorities when designing documents for the territorial development on the strategic and tactical level.","PeriodicalId":47897,"journal":{"name":"Cambridge Journal of Regions Economy and Society","volume":"10 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85503089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","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.2023-1-13
F. Byk, L. Myshkina, M. Kozhevnikov
A modern organisational and technological structure of the energy sector emerged due to the development of distributed energy improving the reliability, efficiency and environmental friendliness of regional power supply systems. The study aims to substantiate the economic benefits of integrating smart local energy systems (SLES) based on distributed energy into regional power supply systems. Using heu-ristic and theoretical methods, the article explores the genesis of SLES and reveals factors that spur their development in regions. Analysis of empirical data from the implemented SLES projects revealed the ac-celerating pace of adoption of distributed energy by various regional economic sectors, allowing us to esti-mate the effects. Municipal smart local energy systems have a priority over those in agriculture and man-ufacturing, since their integration generates systemic effects significant for the region. These effects in-clude increased availability of energy at socially acceptable prices, reduced cross-subsidisation, flexible energy supply through the use of smart technology, and better conditions for small and medium-sized en-terprises. A key factor limiting the implementation of SLES projects is an underdeveloped institutional en-vironment, which could be improved by changing the current rules of the wholesale and retail markets of electricity and capacity. In particular, it might be expedient to include SLES in regional energy systems in order to justify changes in the regulatory framework. The paper presents a comprehensive examination of the properties and characteristics of smart local energy systems and suggests ways to obtain useful eco-nomic effects in the development of regional power supply systems. As for the practical value, the research emphasises the appeal of SLES to investment companies and outlines conditions for a region’s sustaina-ble development.
{"title":"Improving the Stability of power Supply in Regions on the Basis of Smart Local Energy Systems","authors":"F. Byk, L. Myshkina, M. Kozhevnikov","doi":"10.17059/ekon.reg.2023-1-13","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-1-13","url":null,"abstract":"A modern organisational and technological structure of the energy sector emerged due to the development of distributed energy improving the reliability, efficiency and environmental friendliness of regional power supply systems. The study aims to substantiate the economic benefits of integrating smart local energy systems (SLES) based on distributed energy into regional power supply systems. Using heu-ristic and theoretical methods, the article explores the genesis of SLES and reveals factors that spur their development in regions. Analysis of empirical data from the implemented SLES projects revealed the ac-celerating pace of adoption of distributed energy by various regional economic sectors, allowing us to esti-mate the effects. Municipal smart local energy systems have a priority over those in agriculture and man-ufacturing, since their integration generates systemic effects significant for the region. These effects in-clude increased availability of energy at socially acceptable prices, reduced cross-subsidisation, flexible energy supply through the use of smart technology, and better conditions for small and medium-sized en-terprises. A key factor limiting the implementation of SLES projects is an underdeveloped institutional en-vironment, which could be improved by changing the current rules of the wholesale and retail markets of electricity and capacity. In particular, it might be expedient to include SLES in regional energy systems in order to justify changes in the regulatory framework. The paper presents a comprehensive examination of the properties and characteristics of smart local energy systems and suggests ways to obtain useful eco-nomic effects in the development of regional power supply systems. As for the practical value, the research emphasises the appeal of SLES to investment companies and outlines conditions for a region’s sustaina-ble development.","PeriodicalId":47897,"journal":{"name":"Cambridge Journal of Regions Economy and Society","volume":"41 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81304212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","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.2023-2-1
. И.В.ЛутошкинiD, М. С. Рыбина, . IgorV.LutoshkiniD, Maria S. Rybina
Economic globalisation, logistics intensification, world population growth and increasing mobility lead to the emergence of mass diseases, determining the behaviour of various economic agents. The article offers a new tool for analysing regional economic management in conditions of mass diseases, which combines both socio-biological and economic factors in one economic and mathematical model. The proposed model is based on the description of disease dynamics among various population groups (SIR or SIER compartmental models) and corresponding socio-economic changes. Investments in the improvement of hospital beds, in the construction of new hospitals, and in information campaigns to combat the disease are considered as control actions on the economic system. Thus, the regional management system can apply this tool to quantify and compare possible management decisions, taking into account the mutual influence of biological and socio-economic factors. Mathematical models in population biology and epidemiology were analysed in order to construct the tool and assess its parameters by the methods of regression correlation analysis, simulation modelling, and numerical analysis of the differential equation system. In particular, statistical information on the COVID-19 pandemic in Russia and Ulyanovsk oblast for 2020 was examined during the research. The developed software package was utilised to model the presence or absence of restrictive measures during the reviewed period; then, a comparative analysis of these strategies was conducted. The described tool can be adapted to assess the management strategies of various economic agents. It can be further supplemented with quality criteria and appropriate algorithms for selecting optimal strategies to manage regional economy in conditions of mass diseases.
{"title":"Modelling of Regional Economic Management in Conditions of Mass Diseases","authors":". И.В.ЛутошкинiD, М. С. Рыбина, . IgorV.LutoshkiniD, Maria S. Rybina","doi":"10.17059/ekon.reg.2023-2-1","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-2-1","url":null,"abstract":"Economic globalisation, logistics intensification, world population growth and increasing mobility lead to the emergence of mass diseases, determining the behaviour of various economic agents. The article offers a new tool for analysing regional economic management in conditions of mass diseases, which combines both socio-biological and economic factors in one economic and mathematical model. The proposed model is based on the description of disease dynamics among various population groups (SIR or SIER compartmental models) and corresponding socio-economic changes. Investments in the improvement of hospital beds, in the construction of new hospitals, and in information campaigns to combat the disease are considered as control actions on the economic system. Thus, the regional management system can apply this tool to quantify and compare possible management decisions, taking into account the mutual influence of biological and socio-economic factors. Mathematical models in population biology and epidemiology were analysed in order to construct the tool and assess its parameters by the methods of regression correlation analysis, simulation modelling, and numerical analysis of the differential equation system. In particular, statistical information on the COVID-19 pandemic in Russia and Ulyanovsk oblast for 2020 was examined during the research. The developed software package was utilised to model the presence or absence of restrictive measures during the reviewed period; then, a comparative analysis of these strategies was conducted. The described tool can be adapted to assess the management strategies of various economic agents. It can be further supplemented with quality criteria and appropriate algorithms for selecting optimal strategies to manage regional economy in conditions of mass diseases.","PeriodicalId":47897,"journal":{"name":"Cambridge Journal of Regions Economy and Society","volume":"109 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80877652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","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.2023-1-1
Z. Belyaeva, Y. Lopatkova
The world economic development nowadays is characterised by the significance of digital in-novations and sustainable development in all areas of production and management. However, the exist-ing literature still cannot explain how environmental, economic and social factors of sustainable develop-ment corresponding to these innovations affect the new global ecosystem, based on the introduction and adaptation of digital technologies and achievement of the United Nations Sustainable Development Goals (SDGs) at the national level. The article presents the results of the authors’ assessment and classification of countries according to the achievement of the SDGs and implementation of digital innovations in the national and global economy. The empirical analysis utilises the data on the digitalisation performance in-dicators of the Global Innovation Index (GII) and the Sustainable Development Goals Index (SDG Index). The country assessment matrix was classified in terms of digitalisation and sustainable development and tested on a sample of European countries. Cluster analysis of 39 European countries identified four homo-geneous clusters, which have distinctive systemic characteristics: advanced countries, catching-up coun-tries, locomotive countries and leaders in sustainable and digital development. The identified clusters ex-pand the possibilities for substantiating socio-economic and technological strategies at the country — re-gion — industry level. Russia is revealed as one of the eleven catching-up countries. The paper specifies the directions of the strategy to achieve the target digitalisation and sustainable development in the pro-cess of integration of the SDGs into national indicators. The proposed assessment can be used to adjust the state policy for the co-development of digital innovations and sustainable development indicators.
{"title":"Cluster Assessment of European Countries in Terms of Digitalisation and Sustainable Development","authors":"Z. Belyaeva, Y. Lopatkova","doi":"10.17059/ekon.reg.2023-1-1","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-1-1","url":null,"abstract":"The world economic development nowadays is characterised by the significance of digital in-novations and sustainable development in all areas of production and management. However, the exist-ing literature still cannot explain how environmental, economic and social factors of sustainable develop-ment corresponding to these innovations affect the new global ecosystem, based on the introduction and adaptation of digital technologies and achievement of the United Nations Sustainable Development Goals (SDGs) at the national level. The article presents the results of the authors’ assessment and classification of countries according to the achievement of the SDGs and implementation of digital innovations in the national and global economy. The empirical analysis utilises the data on the digitalisation performance in-dicators of the Global Innovation Index (GII) and the Sustainable Development Goals Index (SDG Index). The country assessment matrix was classified in terms of digitalisation and sustainable development and tested on a sample of European countries. Cluster analysis of 39 European countries identified four homo-geneous clusters, which have distinctive systemic characteristics: advanced countries, catching-up coun-tries, locomotive countries and leaders in sustainable and digital development. The identified clusters ex-pand the possibilities for substantiating socio-economic and technological strategies at the country — re-gion — industry level. Russia is revealed as one of the eleven catching-up countries. The paper specifies the directions of the strategy to achieve the target digitalisation and sustainable development in the pro-cess of integration of the SDGs into national indicators. The proposed assessment can be used to adjust the state policy for the co-development of digital innovations and sustainable development indicators.","PeriodicalId":47897,"journal":{"name":"Cambridge Journal of Regions Economy and Society","volume":"139 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86578838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","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.2023-2-21
Sanaa Maswadeh
Governments care about the tax system and pay attention to it not as a tool for collecting money, but rather as a tool of economic reform, so that taxes achieve their financial, economic and social goals, and then achieve tax justice and protect the poor and middle class. Thus, this study came to investigate the effect of the tax revenue structure in Jordan on economics reform indicators (per individual income growth rate, public debt, openness trade, and inflation) as a challenge to the economic reform. The study population consists of the public sector of the ministries and public sector departments responsible for preparing the general budget and the Jordanian Department of Statistics, with the aim of relying on data issued by them during the time period 1990-2019. Multiple regression models were used to study hypotheses. The research results showed that direct tax (income and profits tax) in Jordan did not significantly affect the economic reform indicators, while there was a negative significant impact at a significance level (á ≤ 0.05) of sales tax on the economic reform indicators. Additionally, the study found that there is no significant effect of indirect taxes (property tax and foreign trade) on economic indicators relative to GDP represented in per individual income growth rate, public debt, and inflation. Among the recommendations of the study is that Jordan must develop the country’s public revenues from its own resources in order to reduce dependence on foreign debt.
{"title":"Tax System Reform as a Challenge to Economic Reform: A Case Study of Jordan","authors":"Sanaa Maswadeh","doi":"10.17059/ekon.reg.2023-2-21","DOIUrl":"https://doi.org/10.17059/ekon.reg.2023-2-21","url":null,"abstract":"Governments care about the tax system and pay attention to it not as a tool for collecting money, but rather as a tool of economic reform, so that taxes achieve their financial, economic and social goals, and then achieve tax justice and protect the poor and middle class. Thus, this study came to investigate the effect of the tax revenue structure in Jordan on economics reform indicators (per individual income growth rate, public debt, openness trade, and inflation) as a challenge to the economic reform. The study population consists of the public sector of the ministries and public sector departments responsible for preparing the general budget and the Jordanian Department of Statistics, with the aim of relying on data issued by them during the time period 1990-2019. Multiple regression models were used to study hypotheses. The research results showed that direct tax (income and profits tax) in Jordan did not significantly affect the economic reform indicators, while there was a negative significant impact at a significance level (á ≤ 0.05) of sales tax on the economic reform indicators. Additionally, the study found that there is no significant effect of indirect taxes (property tax and foreign trade) on economic indicators relative to GDP represented in per individual income growth rate, public debt, and inflation. Among the recommendations of the study is that Jordan must develop the country’s public revenues from its own resources in order to reduce dependence on foreign debt.","PeriodicalId":47897,"journal":{"name":"Cambridge Journal of Regions Economy and Society","volume":"40 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74214382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：